notebooks/5_WordEmbeddings.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jXqBicFe_3Dc"
      },
      "source": [
        "# Word Embeddings with Gensim"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "m26InJ0m_3De"
      },
      "outputs": [],
      "source": [
        "%matplotlib notebook\n",
        "import matplotlib.pyplot as plt\n",
        "plt.style.use('ggplot')\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "import numpy as np\n",
        "from sklearn.decomposition import PCA"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kMt7yyaD_3Df"
      },
      "source": [
        "We will use [Gensim](https://radimrehurek.com/gensim/index.html), a package for topic modelling and text similarity, which now exposes some efficient implementations of word embeddings (Word2Vec, GloVe, fastText). This lab provides a first short peek into word embeddings: a much wider topic in itself."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MOS55Ni4_3Dg"
      },
      "source": [
        "### Pre-trained models\n",
        "\n",
        "See here for pre-trained models and available datasets via Gensim: https://github.com/RaRe-Technologies/gensim-data.\n",
        "\n",
        "\n",
        "For this example, refer to: https://radimrehurek.com/gensim/auto_examples/tutorials/run_word2vec.html."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "scrolled": false,
        "id": "IRwC_Nbf_3Dg"
      },
      "outputs": [],
      "source": [
        "# Load a pre-trained model\n",
        "import gensim.downloader as api\n",
        "wv = api.load('glove-wiki-gigaword-100') # Pre-trained model (just the word embeddings) from Wikipedia + Gigaworld\n",
        "# this is a GloVe model\n",
        "# The dimension of these vectors is 100"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VVB4J7Z9_3Dg",
        "outputId": "76807991-2dba-445c-f755-35689d915e36"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "the\n",
            ",\n",
            ".\n",
            "of\n",
            "to\n",
            "and\n",
            "in\n",
            "a\n",
            "\"\n",
            "'s\n",
            "for\n",
            "-\n",
            "that\n",
            "on\n",
            "is\n",
            "was\n",
            "said\n",
            "with\n",
            "he\n",
            "as\n"
          ]
        }
      ],
      "source": [
        "# access the words\n",
        "for i, word in enumerate(wv.vocab):\n",
        "    if i == 20:\n",
        "        break\n",
        "    print(word)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3LX76YRa_3Di",
        "outputId": "4316a07d-d946-4cda-f7bc-9466f31846e6"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[-0.32307  -0.87616   0.21977   0.25268   0.22976   0.7388   -0.37954\n",
            " -0.35307  -0.84369  -1.1113   -0.30266   0.33178  -0.25113   0.30448\n",
            " -0.077491 -0.89815   0.092496 -1.1407   -0.58324   0.66869  -0.23122\n",
            " -0.95855   0.28262  -0.078848  0.75315   0.26584   0.3422   -0.33949\n",
            "  0.95608   0.065641  0.45747   0.39835   0.57965   0.39267  -0.21851\n",
            "  0.58795  -0.55999   0.63368  -0.043983 -0.68731  -0.37841   0.38026\n",
            "  0.61641  -0.88269  -0.12346  -0.37928  -0.38318   0.23868   0.6685\n",
            " -0.43321  -0.11065   0.081723  1.1569    0.78958  -0.21223  -2.3211\n",
            " -0.67806   0.44561   0.65707   0.1045    0.46217   0.19912   0.25802\n",
            "  0.057194  0.53443  -0.43133  -0.34311   0.59789  -0.58417   0.068995\n",
            "  0.23944  -0.85181   0.30379  -0.34177  -0.25746  -0.031101 -0.16285\n",
            "  0.45169  -0.91627   0.64521   0.73281  -0.22752   0.30226   0.044801\n",
            " -0.83741   0.55006  -0.52506  -1.7357    0.4751   -0.70487   0.056939\n",
            " -0.7132    0.089623  0.41394  -1.3363   -0.61915  -0.33089  -0.52881\n",
            "  0.16483  -0.98878 ]\n"
          ]
        }
      ],
      "source": [
        "# access the vectors\n",
        "vec_king = wv['king']\n",
        "print(vec_king)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "nvsK55dq_3Di",
        "outputId": "3d9166f3-e61f-4a70-e291-276c05f4af55"
      },
      "outputs": [
        {
          "ename": "KeyError",
          "evalue": "\"word 'kanliwg' not in vocabulary\"",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-5-c4dca187d750>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# an exception is raised for missing words\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mwv\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"kanliwg\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/anaconda3/envs/uva/lib/python3.8/site-packages/gensim/models/keyedvectors.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, entities)\u001b[0m\n\u001b[1;32m    351\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mentities\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstring_types\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    352\u001b[0m             \u001b[0;31m# allow calls like trained_model['office'], as a shorthand for trained_model[['office']]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 353\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_vector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mentities\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    354\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    355\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mvstack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_vector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mentity\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mentity\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mentities\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/anaconda3/envs/uva/lib/python3.8/site-packages/gensim/models/keyedvectors.py\u001b[0m in \u001b[0;36mget_vector\u001b[0;34m(self, word)\u001b[0m\n\u001b[1;32m    469\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    470\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget_vector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mword\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 471\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mword_vec\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mword\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    472\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    473\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mwords_closer_than\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mw1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mw2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/anaconda3/envs/uva/lib/python3.8/site-packages/gensim/models/keyedvectors.py\u001b[0m in \u001b[0;36mword_vec\u001b[0;34m(self, word, use_norm)\u001b[0m\n\u001b[1;32m    466\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    467\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 468\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"word '%s' not in vocabulary\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mword\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    469\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    470\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget_vector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mword\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: \"word 'kanliwg' not in vocabulary\""
          ]
        }
      ],
      "source": [
        "# an exception is raised for missing words\n",
        "wv[\"kanliwg\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "C3RZeTMb_3Di",
        "outputId": "485c679d-c315-4607-8b05-781ca09090ec"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "'car'\t'minivan'\t0.67\n",
            "'car'\t'bicycle'\t0.69\n",
            "'car'\t'airplane'\t0.65\n",
            "'car'\t'cereal'\t0.12\n",
            "'car'\t'communism'\t0.04\n"
          ]
        }
      ],
      "source": [
        "# similarity queries (default to cosine similarity: 0 least similar, to 1 most similar)\n",
        "pairs = [\n",
        "    ('car', 'minivan'),   # a minivan is a kind of car\n",
        "    ('car', 'bicycle'),   # still a wheeled vehicle\n",
        "    ('car', 'airplane'),  # ok, no wheels, but still a vehicle\n",
        "    ('car', 'cereal'),    # ... and so on\n",
        "    ('car', 'communism'),\n",
        "]\n",
        "for w1, w2 in pairs:\n",
        "    print('%r\\t%r\\t%.2f' % (w1, w2, wv.similarity(w1, w2)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "XKNi_jcI_3Dj",
        "outputId": "c6ca5d27-1e9e-4f39-9710-7d7499be9a57"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.6690627932548523"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# do not trust me:\n",
        "from scipy.spatial.distance import cosine\n",
        "\n",
        "1 - cosine(wv[\"car\"],wv[\"minivan\"]) # note: Gensim computes similarities, here we have it as a distance, hence 1-similarity (when the score goes between 0 and 1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7yralJ-2_3Dj",
        "outputId": "9e5f416c-d8c5-4811-ae99-71325bf3c56b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[('vehicle', 0.8630838394165039),\n",
              " ('truck', 0.8597878217697144),\n",
              " ('cars', 0.837166965007782),\n",
              " ('driver', 0.8185911178588867),\n",
              " ('driving', 0.781263530254364),\n",
              " ('motorcycle', 0.7553157210350037),\n",
              " ('vehicles', 0.7462255954742432),\n",
              " ('parked', 0.7459464073181152),\n",
              " ('bus', 0.7372706532478333),\n",
              " ('taxi', 0.7155268788337708)]"
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# you can also get a list\n",
        "\n",
        "wv.most_similar(\"car\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "trv_AKLS_3Dj",
        "outputId": "4574d7ff-330b-46b9-a67d-36e747082d7c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[('jae-suk', 0.5536853671073914),\n",
              " ('ren?e', 0.5491408109664917),\n",
              " ('aelfric', 0.5432723760604858),\n",
              " ('wiek', 0.5375073552131653),\n",
              " ('zety', 0.5373221039772034),\n",
              " ('wenxue', 0.5362256765365601),\n",
              " ('zibi', 0.5342655181884766),\n",
              " ('taijutsu', 0.5330424308776855),\n",
              " ('anishinaabeg', 0.532688558101654),\n",
              " ('berte', 0.531627893447876)]"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# most dissimilar\n",
        "\n",
        "wv.most_similar(negative=[\"car\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "I9Ey1F2N_3Dk",
        "outputId": "63bbda63-248e-49f1-c33a-e74925a4b3b5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "car\n"
          ]
        }
      ],
      "source": [
        "# finding \"intruders\"\n",
        "\n",
        "print(wv.doesnt_match(\"breakfast car dinner lunch snack\".split()))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Yi2edENA_3Dk"
      },
      "source": [
        "#### Analogies\n",
        "\n",
        "Another contribution of the Wird2Vec original paper was evaluation by analogy: if we sum two related word senses, and subtract a third, do we get what we intuitively should?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jtniyQlt_3Dk"
      },
      "outputs": [],
      "source": [
        "def analogy(x1, x2, x3):\n",
        "    result = wv.most_similar(positive=[x1, x2], negative=[x3])\n",
        "    return result[0][0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Fpw-alOZ_3Dl",
        "outputId": "7a70863f-b6ba-4a56-f166-0a9e7f8df702"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'queen'"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "analogy(\"king\",\"woman\",\"man\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vP7J00W6_3Dl",
        "outputId": "6c57add3-4833-4602-e3f2-94aede8f03b3"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'noodles'"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "analogy(\"pasta\",\"japan\",\"italy\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Dug1Pj4q_3Dl",
        "outputId": "4b171f16-a044-4948-842a-6f003bba5ef8"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'britain'"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "analogy(\"japan\",\"london\",\"tokio\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jTge9nLr_3Dm",
        "outputId": "7f1805dc-590b-4db1-ccc9-8b8b9de08e5c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'snow'"
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "analogy(\"water\",\"ice\",\"liquid\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Tj48kEcu_3Dm"
      },
      "source": [
        "### Training a model\n",
        "\n",
        "https://radimrehurek.com/gensim/auto_examples/tutorials/run_word2vec.html#training-your-own-model."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pk0UlXtZ_3Dm",
        "outputId": "58761962-96f5-40cf-8b78-04ccde81d7fa"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'/Users/giovannicolavizza/gensim-data/text8/text8.gz'"
            ]
          },
          "execution_count": 24,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import gensim.downloader as api\n",
        "text8_path = api.load('text8', return_path=True) # a slice of Wikipedia in English\n",
        "text8_path"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "NQtqN8W__3Dn",
        "outputId": "c58b4338-1ee0-4fe0-f7c1-79660ed4f715"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Word2Vec(vocab=71290, size=100, alpha=0.05)\n"
          ]
        }
      ],
      "source": [
        "from gensim.models import Word2Vec, KeyedVectors\n",
        "from gensim.models.word2vec import Text8Corpus\n",
        "\n",
        "# Using params from Word2Vec_FastText_Comparison\n",
        "params = {\n",
        "    'size': 100, # dimension of embeddings\n",
        "    'window': 5, # window -/+ before and after focus word\n",
        "    'iter': 5, # number of iterations over the corpus\n",
        "    'min_count': 5, # filter on words whose frequency is below this count\n",
        "    'sg': 0, # use the skip-gram (1) or the CBOW (0) mode. In class, we presented the CBOW (predict context given focus words). See optional materials for the skip-gram (predict focus given context)\n",
        "    'negative': 5, # how many negative samples to use (see optional class contents too)\n",
        "    'workers': 4, # how many cores to use\n",
        "    'alpha': 0.05 # initial learning rate for SGD. This is lambda in the class notes\n",
        "}\n",
        "model = Word2Vec(Text8Corpus(text8_path), **params)\n",
        "print(model)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7XhIOJ5e_3Dn",
        "outputId": "69671cb9-d4bb-43e0-800f-79311c2baa42"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "'car'\t'minivan'\t0.36\n",
            "'car'\t'bicycle'\t0.61\n",
            "'car'\t'airplane'\t0.46\n",
            "'car'\t'cereal'\t0.14\n",
            "'car'\t'communism'\t-0.00\n"
          ]
        }
      ],
      "source": [
        "# similarity queries (default to cosine similarity: 0 least similar, to 1 most similar)\n",
        "pairs = [\n",
        "    ('car', 'minivan'),   # a minivan is a kind of car\n",
        "    ('car', 'bicycle'),   # still a wheeled vehicle\n",
        "    ('car', 'airplane'),  # ok, no wheels, but still a vehicle\n",
        "    ('car', 'cereal'),    # ... and so on\n",
        "    ('car', 'communism'),\n",
        "]\n",
        "for w1, w2 in pairs:\n",
        "    print('%r\\t%r\\t%.2f' % (w1, w2, model.wv.similarity(w1, w2)))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O7W50aLC_3Dn"
      },
      "source": [
        "How to build an index for similarity queries: https://radimrehurek.com/gensim/auto_examples/tutorials/run_annoy.html."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s5giEYjJ_3Do"
      },
      "source": [
        "### Visualization\n",
        "\n",
        "From: http://web.stanford.edu/class/cs224n/.\n",
        "\n",
        "We use Principal Component Analysis (PCA) to visualize vectors in high dimensions in 2d: https://en.wikipedia.org/wiki/Principal_component_analysis. PCA corresponds to doing an eigenvalue decomposition of the data correlation matrix, or an SVD of the data matrix (our word vectors). You can think of it as creating orthogonal and variance-maximizing linear combinations of features (the original embedding dimensions we have)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "35rEygTO_3Do"
      },
      "outputs": [],
      "source": [
        "def display_pca_scatterplot(model, words=None, sample=0):\n",
        "    if words == None:\n",
        "        if sample > 0:\n",
        "            words = np.random.choice(list(model.vocab.keys()), sample)\n",
        "        else:\n",
        "            words = [ word for word in model.vocab ]\n",
        "        \n",
        "    word_vectors = np.array([model[w] for w in words])\n",
        "\n",
        "    # do PCA on the selected embeddings\n",
        "    twodim = PCA().fit_transform(word_vectors)[:,:2]\n",
        "    \n",
        "    plt.figure(figsize=(6,6))\n",
        "    plt.scatter(twodim[:,0], twodim[:,1], edgecolors='k', c='r')\n",
        "    for word, (x,y) in zip(words, twodim):\n",
        "        plt.text(x+0.05, y+0.05, word)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-hxJo-zY_3Do",
        "outputId": "5f51e8b7-bbbe-4d42-a0e5-fb13ba37df1e"
      },
      "outputs": [
        {
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              "window.mpl = {};\n",
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              "    this.context = canvas.getContext('2d');\n",
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              "\n",
              "            rubberband_canvas.setAttribute('width', width);\n",
              "            rubberband_canvas.setAttribute('height', height);\n",
              "\n",
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              "            // that occurs as the element is placed into the DOM, which should\n",
              "            // otherwise not happen due to the minimum size styling.\n",
              "            if (width != 0 && height != 0) {\n",
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              "\n",
              "    window.setTimeout(set_focus, 100);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var toolbar = document.createElement('div');\n",
              "    toolbar.classList = 'mpl-toolbar';\n",
              "    this.root.appendChild(toolbar);\n",
              "\n",
              "    function on_click_closure(name) {\n",
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              "            return fig.toolbar_button_onclick(name);\n",
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              "\n",
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              "\n",
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              "    var buttonGroup = document.createElement('div');\n",
              "    buttonGroup.classList = 'mpl-button-group';\n",
              "    for (var toolbar_ind in mpl.toolbar_items) {\n",
              "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
              "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
              "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
              "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
              "\n",
              "        if (!name) {\n",
              "            /* Instead of a spacer, we start a new button group. */\n",
              "            if (buttonGroup.hasChildNodes()) {\n",
              "                toolbar.appendChild(buttonGroup);\n",
              "            }\n",
              "            buttonGroup = document.createElement('div');\n",
              "            buttonGroup.classList = 'mpl-button-group';\n",
              "            continue;\n",
              "        }\n",
              "\n",
              "        var button = (fig.buttons[name] = document.createElement('button'));\n",
              "        button.classList = 'mpl-widget';\n",
              "        button.setAttribute('role', 'button');\n",
              "        button.setAttribute('aria-disabled', 'false');\n",
              "        button.addEventListener('click', on_click_closure(method_name));\n",
              "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
              "\n",
              "        var icon_img = document.createElement('img');\n",
              "        icon_img.src = '_images/' + image + '.png';\n",
              "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
              "        icon_img.alt = tooltip;\n",
              "        button.appendChild(icon_img);\n",
              "\n",
              "        buttonGroup.appendChild(button);\n",
              "    }\n",
              "\n",
              "    if (buttonGroup.hasChildNodes()) {\n",
              "        toolbar.appendChild(buttonGroup);\n",
              "    }\n",
              "\n",
              "    var fmt_picker = document.createElement('select');\n",
              "    fmt_picker.classList = 'mpl-widget';\n",
              "    toolbar.appendChild(fmt_picker);\n",
              "    this.format_dropdown = fmt_picker;\n",
              "\n",
              "    for (var ind in mpl.extensions) {\n",
              "        var fmt = mpl.extensions[ind];\n",
              "        var option = document.createElement('option');\n",
              "        option.selected = fmt === mpl.default_extension;\n",
              "        option.innerHTML = fmt;\n",
              "        fmt_picker.appendChild(option);\n",
              "    }\n",
              "\n",
              "    var status_bar = document.createElement('span');\n",
              "    status_bar.classList = 'mpl-message';\n",
              "    toolbar.appendChild(status_bar);\n",
              "    this.message = status_bar;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
              "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
              "    // which will in turn request a refresh of the image.\n",
              "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.send_message = function (type, properties) {\n",
              "    properties['type'] = type;\n",
              "    properties['figure_id'] = this.id;\n",
              "    this.ws.send(JSON.stringify(properties));\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.send_draw_message = function () {\n",
              "    if (!this.waiting) {\n",
              "        this.waiting = true;\n",
              "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
              "    var format_dropdown = fig.format_dropdown;\n",
              "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
              "    fig.ondownload(fig, format);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
              "    var size = msg['size'];\n",
              "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
              "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
              "        fig.send_message('refresh', {});\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
              "    var x0 = msg['x0'] / fig.ratio;\n",
              "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
              "    var x1 = msg['x1'] / fig.ratio;\n",
              "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
              "    x0 = Math.floor(x0) + 0.5;\n",
              "    y0 = Math.floor(y0) + 0.5;\n",
              "    x1 = Math.floor(x1) + 0.5;\n",
              "    y1 = Math.floor(y1) + 0.5;\n",
              "    var min_x = Math.min(x0, x1);\n",
              "    var min_y = Math.min(y0, y1);\n",
              "    var width = Math.abs(x1 - x0);\n",
              "    var height = Math.abs(y1 - y0);\n",
              "\n",
              "    fig.rubberband_context.clearRect(\n",
              "        0,\n",
              "        0,\n",
              "        fig.canvas.width / fig.ratio,\n",
              "        fig.canvas.height / fig.ratio\n",
              "    );\n",
              "\n",
              "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
              "    // Updates the figure title.\n",
              "    fig.header.textContent = msg['label'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
              "    var cursor = msg['cursor'];\n",
              "    switch (cursor) {\n",
              "        case 0:\n",
              "            cursor = 'pointer';\n",
              "            break;\n",
              "        case 1:\n",
              "            cursor = 'default';\n",
              "            break;\n",
              "        case 2:\n",
              "            cursor = 'crosshair';\n",
              "            break;\n",
              "        case 3:\n",
              "            cursor = 'move';\n",
              "            break;\n",
              "    }\n",
              "    fig.rubberband_canvas.style.cursor = cursor;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
              "    fig.message.textContent = msg['message'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
              "    // Request the server to send over a new figure.\n",
              "    fig.send_draw_message();\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
              "    fig.image_mode = msg['mode'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
              "    for (var key in msg) {\n",
              "        if (!(key in fig.buttons)) {\n",
              "            continue;\n",
              "        }\n",
              "        fig.buttons[key].disabled = !msg[key];\n",
              "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
              "    if (msg['mode'] === 'PAN') {\n",
              "        fig.buttons['Pan'].classList.add('active');\n",
              "        fig.buttons['Zoom'].classList.remove('active');\n",
              "    } else if (msg['mode'] === 'ZOOM') {\n",
              "        fig.buttons['Pan'].classList.remove('active');\n",
              "        fig.buttons['Zoom'].classList.add('active');\n",
              "    } else {\n",
              "        fig.buttons['Pan'].classList.remove('active');\n",
              "        fig.buttons['Zoom'].classList.remove('active');\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function () {\n",
              "    // Called whenever the canvas gets updated.\n",
              "    this.send_message('ack', {});\n",
              "};\n",
              "\n",
              "// A function to construct a web socket function for onmessage handling.\n",
              "// Called in the figure constructor.\n",
              "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
              "    return function socket_on_message(evt) {\n",
              "        if (evt.data instanceof Blob) {\n",
              "            /* FIXME: We get \"Resource interpreted as Image but\n",
              "             * transferred with MIME type text/plain:\" errors on\n",
              "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
              "             * to be part of the websocket stream */\n",
              "            evt.data.type = 'image/png';\n",
              "\n",
              "            /* Free the memory for the previous frames */\n",
              "            if (fig.imageObj.src) {\n",
              "                (window.URL || window.webkitURL).revokeObjectURL(\n",
              "                    fig.imageObj.src\n",
              "                );\n",
              "            }\n",
              "\n",
              "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
              "                evt.data\n",
              "            );\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        } else if (\n",
              "            typeof evt.data === 'string' &&\n",
              "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
              "        ) {\n",
              "            fig.imageObj.src = evt.data;\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        }\n",
              "\n",
              "        var msg = JSON.parse(evt.data);\n",
              "        var msg_type = msg['type'];\n",
              "\n",
              "        // Call the  \"handle_{type}\" callback, which takes\n",
              "        // the figure and JSON message as its only arguments.\n",
              "        try {\n",
              "            var callback = fig['handle_' + msg_type];\n",
              "        } catch (e) {\n",
              "            console.log(\n",
              "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
              "                msg\n",
              "            );\n",
              "            return;\n",
              "        }\n",
              "\n",
              "        if (callback) {\n",
              "            try {\n",
              "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
              "                callback(fig, msg);\n",
              "            } catch (e) {\n",
              "                console.log(\n",
              "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
              "                    e,\n",
              "                    e.stack,\n",
              "                    msg\n",
              "                );\n",
              "            }\n",
              "        }\n",
              "    };\n",
              "};\n",
              "\n",
              "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
              "mpl.findpos = function (e) {\n",
              "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
              "    var targ;\n",
              "    if (!e) {\n",
              "        e = window.event;\n",
              "    }\n",
              "    if (e.target) {\n",
              "        targ = e.target;\n",
              "    } else if (e.srcElement) {\n",
              "        targ = e.srcElement;\n",
              "    }\n",
              "    if (targ.nodeType === 3) {\n",
              "        // defeat Safari bug\n",
              "        targ = targ.parentNode;\n",
              "    }\n",
              "\n",
              "    // pageX,Y are the mouse positions relative to the document\n",
              "    var boundingRect = targ.getBoundingClientRect();\n",
              "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
              "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
              "\n",
              "    return { x: x, y: y };\n",
              "};\n",
              "\n",
              "/*\n",
              " * return a copy of an object with only non-object keys\n",
              " * we need this to avoid circular references\n",
              " * http://stackoverflow.com/a/24161582/3208463\n",
              " */\n",
              "function simpleKeys(original) {\n",
              "    return Object.keys(original).reduce(function (obj, key) {\n",
              "        if (typeof original[key] !== 'object') {\n",
              "            obj[key] = original[key];\n",
              "        }\n",
              "        return obj;\n",
              "    }, {});\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.mouse_event = function (event, name) {\n",
              "    var canvas_pos = mpl.findpos(event);\n",
              "\n",
              "    if (name === 'button_press') {\n",
              "        this.canvas.focus();\n",
              "        this.canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    var x = canvas_pos.x * this.ratio;\n",
              "    var y = canvas_pos.y * this.ratio;\n",
              "\n",
              "    this.send_message(name, {\n",
              "        x: x,\n",
              "        y: y,\n",
              "        button: event.button,\n",
              "        step: event.step,\n",
              "        guiEvent: simpleKeys(event),\n",
              "    });\n",
              "\n",
              "    /* This prevents the web browser from automatically changing to\n",
              "     * the text insertion cursor when the button is pressed.  We want\n",
              "     * to control all of the cursor setting manually through the\n",
              "     * 'cursor' event from matplotlib */\n",
              "    event.preventDefault();\n",
              "    return false;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
              "    // Handle any extra behaviour associated with a key event\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.key_event = function (event, name) {\n",
              "    // Prevent repeat events\n",
              "    if (name === 'key_press') {\n",
              "        if (event.which === this._key) {\n",
              "            return;\n",
              "        } else {\n",
              "            this._key = event.which;\n",
              "        }\n",
              "    }\n",
              "    if (name === 'key_release') {\n",
              "        this._key = null;\n",
              "    }\n",
              "\n",
              "    var value = '';\n",
              "    if (event.ctrlKey && event.which !== 17) {\n",
              "        value += 'ctrl+';\n",
              "    }\n",
              "    if (event.altKey && event.which !== 18) {\n",
              "        value += 'alt+';\n",
              "    }\n",
              "    if (event.shiftKey && event.which !== 16) {\n",
              "        value += 'shift+';\n",
              "    }\n",
              "\n",
              "    value += 'k';\n",
              "    value += event.which.toString();\n",
              "\n",
              "    this._key_event_extra(event, name);\n",
              "\n",
              "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
              "    return false;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
              "    if (name === 'download') {\n",
              "        this.handle_save(this, null);\n",
              "    } else {\n",
              "        this.send_message('toolbar_button', { name: name });\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
              "    this.message.textContent = tooltip;\n",
              "};\n",
              "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
              "\n",
              "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
              "\n",
              "mpl.default_extension = \"png\";/* global mpl */\n",
              "\n",
              "var comm_websocket_adapter = function (comm) {\n",
              "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
              "    // object with the appropriate methods. Currently this is a non binary\n",
              "    // socket, so there is still some room for performance tuning.\n",
              "    var ws = {};\n",
              "\n",
              "    ws.close = function () {\n",
              "        comm.close();\n",
              "    };\n",
              "    ws.send = function (m) {\n",
              "        //console.log('sending', m);\n",
              "        comm.send(m);\n",
              "    };\n",
              "    // Register the callback with on_msg.\n",
              "    comm.on_msg(function (msg) {\n",
              "        //console.log('receiving', msg['content']['data'], msg);\n",
              "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
              "        ws.onmessage(msg['content']['data']);\n",
              "    });\n",
              "    return ws;\n",
              "};\n",
              "\n",
              "mpl.mpl_figure_comm = function (comm, msg) {\n",
              "    // This is the function which gets called when the mpl process\n",
              "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
              "\n",
              "    var id = msg.content.data.id;\n",
              "    // Get hold of the div created by the display call when the Comm\n",
              "    // socket was opened in Python.\n",
              "    var element = document.getElementById(id);\n",
              "    var ws_proxy = comm_websocket_adapter(comm);\n",
              "\n",
              "    function ondownload(figure, _format) {\n",
              "        window.open(figure.canvas.toDataURL());\n",
              "    }\n",
              "\n",
              "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
              "\n",
              "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
              "    // web socket which is closed, not our websocket->open comm proxy.\n",
              "    ws_proxy.onopen();\n",
              "\n",
              "    fig.parent_element = element;\n",
              "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
              "    if (!fig.cell_info) {\n",
              "        console.error('Failed to find cell for figure', id, fig);\n",
              "        return;\n",
              "    }\n",
              "    fig.cell_info[0].output_area.element.one(\n",
              "        'cleared',\n",
              "        { fig: fig },\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
              "    var width = fig.canvas.width / fig.ratio;\n",
              "    fig.cell_info[0].output_area.element.off(\n",
              "        'cleared',\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "\n",
              "    // Update the output cell to use the data from the current canvas.\n",
              "    fig.push_to_output();\n",
              "    var dataURL = fig.canvas.toDataURL();\n",
              "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
              "    // the notebook keyboard shortcuts fail.\n",
              "    IPython.keyboard_manager.enable();\n",
              "    fig.parent_element.innerHTML =\n",
              "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
              "    fig.close_ws(fig, msg);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
              "    fig.send_message('closing', msg);\n",
              "    // fig.ws.close()\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
              "    // Turn the data on the canvas into data in the output cell.\n",
              "    var width = this.canvas.width / this.ratio;\n",
              "    var dataURL = this.canvas.toDataURL();\n",
              "    this.cell_info[1]['text/html'] =\n",
              "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function () {\n",
              "    // Tell IPython that the notebook contents must change.\n",
              "    IPython.notebook.set_dirty(true);\n",
              "    this.send_message('ack', {});\n",
              "    var fig = this;\n",
              "    // Wait a second, then push the new image to the DOM so\n",
              "    // that it is saved nicely (might be nice to debounce this).\n",
              "    setTimeout(function () {\n",
              "        fig.push_to_output();\n",
              "    }, 1000);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var toolbar = document.createElement('div');\n",
              "    toolbar.classList = 'btn-toolbar';\n",
              "    this.root.appendChild(toolbar);\n",
              "\n",
              "    function on_click_closure(name) {\n",
              "        return function (_event) {\n",
              "            return fig.toolbar_button_onclick(name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    function on_mouseover_closure(tooltip) {\n",
              "        return function (event) {\n",
              "            if (!event.currentTarget.disabled) {\n",
              "                return fig.toolbar_button_onmouseover(tooltip);\n",
              "            }\n",
              "        };\n",
              "    }\n",
              "\n",
              "    fig.buttons = {};\n",
              "    var buttonGroup = document.createElement('div');\n",
              "    buttonGroup.classList = 'btn-group';\n",
              "    var button;\n",
              "    for (var toolbar_ind in mpl.toolbar_items) {\n",
              "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
              "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
              "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
              "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
              "\n",
              "        if (!name) {\n",
              "            /* Instead of a spacer, we start a new button group. */\n",
              "            if (buttonGroup.hasChildNodes()) {\n",
              "                toolbar.appendChild(buttonGroup);\n",
              "            }\n",
              "            buttonGroup = document.createElement('div');\n",
              "            buttonGroup.classList = 'btn-group';\n",
              "            continue;\n",
              "        }\n",
              "\n",
              "        button = fig.buttons[name] = document.createElement('button');\n",
              "        button.classList = 'btn btn-default';\n",
              "        button.href = '#';\n",
              "        button.title = name;\n",
              "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
              "        button.addEventListener('click', on_click_closure(method_name));\n",
              "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
              "        buttonGroup.appendChild(button);\n",
              "    }\n",
              "\n",
              "    if (buttonGroup.hasChildNodes()) {\n",
              "        toolbar.appendChild(buttonGroup);\n",
              "    }\n",
              "\n",
              "    // Add the status bar.\n",
              "    var status_bar = document.createElement('span');\n",
              "    status_bar.classList = 'mpl-message pull-right';\n",
              "    toolbar.appendChild(status_bar);\n",
              "    this.message = status_bar;\n",
              "\n",
              "    // Add the close button to the window.\n",
              "    var buttongrp = document.createElement('div');\n",
              "    buttongrp.classList = 'btn-group inline pull-right';\n",
              "    button = document.createElement('button');\n",
              "    button.classList = 'btn btn-mini btn-primary';\n",
              "    button.href = '#';\n",
              "    button.title = 'Stop Interaction';\n",
              "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
              "    button.addEventListener('click', function (_evt) {\n",
              "        fig.handle_close(fig, {});\n",
              "    });\n",
              "    button.addEventListener(\n",
              "        'mouseover',\n",
              "        on_mouseover_closure('Stop Interaction')\n",
              "    );\n",
              "    buttongrp.appendChild(button);\n",
              "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
              "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
              "    var fig = event.data.fig;\n",
              "    fig.close_ws(fig, {});\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function (el) {\n",
              "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
              "    // this is important to make the div 'focusable\n",
              "    el.setAttribute('tabindex', 0);\n",
              "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
              "    // off when our div gets focus\n",
              "\n",
              "    // location in version 3\n",
              "    if (IPython.notebook.keyboard_manager) {\n",
              "        IPython.notebook.keyboard_manager.register_events(el);\n",
              "    } else {\n",
              "        // location in version 2\n",
              "        IPython.keyboard_manager.register_events(el);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
              "    var manager = IPython.notebook.keyboard_manager;\n",
              "    if (!manager) {\n",
              "        manager = IPython.keyboard_manager;\n",
              "    }\n",
              "\n",
              "    // Check for shift+enter\n",
              "    if (event.shiftKey && event.which === 13) {\n",
              "        this.canvas_div.blur();\n",
              "        // select the cell after this one\n",
              "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
              "        IPython.notebook.select(index + 1);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
              "    fig.ondownload(fig, null);\n",
              "};\n",
              "\n",
              "mpl.find_output_cell = function (html_output) {\n",
              "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
              "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
              "    // IPython event is triggered only after the cells have been serialised, which for\n",
              "    // our purposes (turning an active figure into a static one), is too late.\n",
              "    var cells = IPython.notebook.get_cells();\n",
              "    var ncells = cells.length;\n",
              "    for (var i = 0; i < ncells; i++) {\n",
              "        var cell = cells[i];\n",
              "        if (cell.cell_type === 'code') {\n",
              "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
              "                var data = cell.output_area.outputs[j];\n",
              "                if (data.data) {\n",
              "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
              "                    data = data.data;\n",
              "                }\n",
              "                if (data['text/html'] === html_output) {\n",
              "                    return [cell, data, j];\n",
              "                }\n",
              "            }\n",
              "        }\n",
              "    }\n",
              "};\n",
              "\n",
              "// Register the function which deals with the matplotlib target/channel.\n",
              "// The kernel may be null if the page has been refreshed.\n",
              "if (IPython.notebook.kernel !== null) {\n",
              "    IPython.notebook.kernel.comm_manager.register_target(\n",
              "        'matplotlib',\n",
              "        mpl.mpl_figure_comm\n",
              "    );\n",
              "}\n"
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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\" width=\"600\">"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "display_pca_scatterplot(wv, \n",
        "                        ['coffee', 'tea', 'beer', 'wine', 'brandy', 'rum', 'champagne', 'water',\n",
        "                         'spaghetti', 'borscht', 'hamburger', 'pizza', 'falafel', 'sushi', 'meatballs',\n",
        "                         'dog', 'horse', 'cat', 'monkey', 'parrot', 'koala', 'lizard',\n",
        "                         'frog', 'toad', 'monkey', 'ape', 'kangaroo', 'wombat', 'wolf',\n",
        "                         'france', 'germany', 'hungary', 'luxembourg', 'australia', 'fiji', 'china',\n",
        "                         'homework', 'assignment', 'problem', 'exam', 'test', 'class',\n",
        "                         'school', 'college', 'university', 'institute'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "uQmBA3MI_3Do",
        "outputId": "fb2ca43d-a429-4fd8-94a2-0e9d2617ee15"
      },
      "outputs": [
        {
          "data": {
            "application/javascript": [
              "/* Put everything inside the global mpl namespace */\n",
              "/* global mpl */\n",
              "window.mpl = {};\n",
              "\n",
              "mpl.get_websocket_type = function () {\n",
              "    if (typeof WebSocket !== 'undefined') {\n",
              "        return WebSocket;\n",
              "    } else if (typeof MozWebSocket !== 'undefined') {\n",
              "        return MozWebSocket;\n",
              "    } else {\n",
              "        alert(\n",
              "            'Your browser does not have WebSocket support. ' +\n",
              "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
              "                'Firefox 4 and 5 are also supported but you ' +\n",
              "                'have to enable WebSockets in about:config.'\n",
              "        );\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
              "    this.id = figure_id;\n",
              "\n",
              "    this.ws = websocket;\n",
              "\n",
              "    this.supports_binary = this.ws.binaryType !== undefined;\n",
              "\n",
              "    if (!this.supports_binary) {\n",
              "        var warnings = document.getElementById('mpl-warnings');\n",
              "        if (warnings) {\n",
              "            warnings.style.display = 'block';\n",
              "            warnings.textContent =\n",
              "                'This browser does not support binary websocket messages. ' +\n",
              "                'Performance may be slow.';\n",
              "        }\n",
              "    }\n",
              "\n",
              "    this.imageObj = new Image();\n",
              "\n",
              "    this.context = undefined;\n",
              "    this.message = undefined;\n",
              "    this.canvas = undefined;\n",
              "    this.rubberband_canvas = undefined;\n",
              "    this.rubberband_context = undefined;\n",
              "    this.format_dropdown = undefined;\n",
              "\n",
              "    this.image_mode = 'full';\n",
              "\n",
              "    this.root = document.createElement('div');\n",
              "    this.root.setAttribute('style', 'display: inline-block');\n",
              "    this._root_extra_style(this.root);\n",
              "\n",
              "    parent_element.appendChild(this.root);\n",
              "\n",
              "    this._init_header(this);\n",
              "    this._init_canvas(this);\n",
              "    this._init_toolbar(this);\n",
              "\n",
              "    var fig = this;\n",
              "\n",
              "    this.waiting = false;\n",
              "\n",
              "    this.ws.onopen = function () {\n",
              "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
              "        fig.send_message('send_image_mode', {});\n",
              "        if (fig.ratio !== 1) {\n",
              "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
              "        }\n",
              "        fig.send_message('refresh', {});\n",
              "    };\n",
              "\n",
              "    this.imageObj.onload = function () {\n",
              "        if (fig.image_mode === 'full') {\n",
              "            // Full images could contain transparency (where diff images\n",
              "            // almost always do), so we need to clear the canvas so that\n",
              "            // there is no ghosting.\n",
              "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
              "        }\n",
              "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
              "    };\n",
              "\n",
              "    this.imageObj.onunload = function () {\n",
              "        fig.ws.close();\n",
              "    };\n",
              "\n",
              "    this.ws.onmessage = this._make_on_message_function(this);\n",
              "\n",
              "    this.ondownload = ondownload;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_header = function () {\n",
              "    var titlebar = document.createElement('div');\n",
              "    titlebar.classList =\n",
              "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
              "    var titletext = document.createElement('div');\n",
              "    titletext.classList = 'ui-dialog-title';\n",
              "    titletext.setAttribute(\n",
              "        'style',\n",
              "        'width: 100%; text-align: center; padding: 3px;'\n",
              "    );\n",
              "    titlebar.appendChild(titletext);\n",
              "    this.root.appendChild(titlebar);\n",
              "    this.header = titletext;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
              "\n",
              "mpl.figure.prototype._init_canvas = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
              "    canvas_div.setAttribute(\n",
              "        'style',\n",
              "        'border: 1px solid #ddd;' +\n",
              "            'box-sizing: content-box;' +\n",
              "            'clear: both;' +\n",
              "            'min-height: 1px;' +\n",
              "            'min-width: 1px;' +\n",
              "            'outline: 0;' +\n",
              "            'overflow: hidden;' +\n",
              "            'position: relative;' +\n",
              "            'resize: both;'\n",
              "    );\n",
              "\n",
              "    function on_keyboard_event_closure(name) {\n",
              "        return function (event) {\n",
              "            return fig.key_event(event, name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    canvas_div.addEventListener(\n",
              "        'keydown',\n",
              "        on_keyboard_event_closure('key_press')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'keyup',\n",
              "        on_keyboard_event_closure('key_release')\n",
              "    );\n",
              "\n",
              "    this._canvas_extra_style(canvas_div);\n",
              "    this.root.appendChild(canvas_div);\n",
              "\n",
              "    var canvas = (this.canvas = document.createElement('canvas'));\n",
              "    canvas.classList.add('mpl-canvas');\n",
              "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
              "\n",
              "    this.context = canvas.getContext('2d');\n",
              "\n",
              "    var backingStore =\n",
              "        this.context.backingStorePixelRatio ||\n",
              "        this.context.webkitBackingStorePixelRatio ||\n",
              "        this.context.mozBackingStorePixelRatio ||\n",
              "        this.context.msBackingStorePixelRatio ||\n",
              "        this.context.oBackingStorePixelRatio ||\n",
              "        this.context.backingStorePixelRatio ||\n",
              "        1;\n",
              "\n",
              "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
              "    if (this.ratio !== 1) {\n",
              "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
              "    }\n",
              "\n",
              "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
              "        'canvas'\n",
              "    ));\n",
              "    rubberband_canvas.setAttribute(\n",
              "        'style',\n",
              "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
              "    );\n",
              "\n",
              "    var resizeObserver = new ResizeObserver(function (entries) {\n",
              "        var nentries = entries.length;\n",
              "        for (var i = 0; i < nentries; i++) {\n",
              "            var entry = entries[i];\n",
              "            var width, height;\n",
              "            if (entry.contentBoxSize) {\n",
              "                if (entry.contentBoxSize instanceof Array) {\n",
              "                    // Chrome 84 implements new version of spec.\n",
              "                    width = entry.contentBoxSize[0].inlineSize;\n",
              "                    height = entry.contentBoxSize[0].blockSize;\n",
              "                } else {\n",
              "                    // Firefox implements old version of spec.\n",
              "                    width = entry.contentBoxSize.inlineSize;\n",
              "                    height = entry.contentBoxSize.blockSize;\n",
              "                }\n",
              "            } else {\n",
              "                // Chrome <84 implements even older version of spec.\n",
              "                width = entry.contentRect.width;\n",
              "                height = entry.contentRect.height;\n",
              "            }\n",
              "\n",
              "            // Keep the size of the canvas and rubber band canvas in sync with\n",
              "            // the canvas container.\n",
              "            if (entry.devicePixelContentBoxSize) {\n",
              "                // Chrome 84 implements new version of spec.\n",
              "                canvas.setAttribute(\n",
              "                    'width',\n",
              "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
              "                );\n",
              "                canvas.setAttribute(\n",
              "                    'height',\n",
              "                    entry.devicePixelContentBoxSize[0].blockSize\n",
              "                );\n",
              "            } else {\n",
              "                canvas.setAttribute('width', width * fig.ratio);\n",
              "                canvas.setAttribute('height', height * fig.ratio);\n",
              "            }\n",
              "            canvas.setAttribute(\n",
              "                'style',\n",
              "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
              "            );\n",
              "\n",
              "            rubberband_canvas.setAttribute('width', width);\n",
              "            rubberband_canvas.setAttribute('height', height);\n",
              "\n",
              "            // And update the size in Python. We ignore the initial 0/0 size\n",
              "            // that occurs as the element is placed into the DOM, which should\n",
              "            // otherwise not happen due to the minimum size styling.\n",
              "            if (width != 0 && height != 0) {\n",
              "                fig.request_resize(width, height);\n",
              "            }\n",
              "        }\n",
              "    });\n",
              "    resizeObserver.observe(canvas_div);\n",
              "\n",
              "    function on_mouse_event_closure(name) {\n",
              "        return function (event) {\n",
              "            return fig.mouse_event(event, name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    rubberband_canvas.addEventListener(\n",
              "        'mousedown',\n",
              "        on_mouse_event_closure('button_press')\n",
              "    );\n",
              "    rubberband_canvas.addEventListener(\n",
              "        'mouseup',\n",
              "        on_mouse_event_closure('button_release')\n",
              "    );\n",
              "    // Throttle sequential mouse events to 1 every 20ms.\n",
              "    rubberband_canvas.addEventListener(\n",
              "        'mousemove',\n",
              "        on_mouse_event_closure('motion_notify')\n",
              "    );\n",
              "\n",
              "    rubberband_canvas.addEventListener(\n",
              "        'mouseenter',\n",
              "        on_mouse_event_closure('figure_enter')\n",
              "    );\n",
              "    rubberband_canvas.addEventListener(\n",
              "        'mouseleave',\n",
              "        on_mouse_event_closure('figure_leave')\n",
              "    );\n",
              "\n",
              "    canvas_div.addEventListener('wheel', function (event) {\n",
              "        if (event.deltaY < 0) {\n",
              "            event.step = 1;\n",
              "        } else {\n",
              "            event.step = -1;\n",
              "        }\n",
              "        on_mouse_event_closure('scroll')(event);\n",
              "    });\n",
              "\n",
              "    canvas_div.appendChild(canvas);\n",
              "    canvas_div.appendChild(rubberband_canvas);\n",
              "\n",
              "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
              "    this.rubberband_context.strokeStyle = '#000000';\n",
              "\n",
              "    this._resize_canvas = function (width, height, forward) {\n",
              "        if (forward) {\n",
              "            canvas_div.style.width = width + 'px';\n",
              "            canvas_div.style.height = height + 'px';\n",
              "        }\n",
              "    };\n",
              "\n",
              "    // Disable right mouse context menu.\n",
              "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
              "        event.preventDefault();\n",
              "        return false;\n",
              "    });\n",
              "\n",
              "    function set_focus() {\n",
              "        canvas.focus();\n",
              "        canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    window.setTimeout(set_focus, 100);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var toolbar = document.createElement('div');\n",
              "    toolbar.classList = 'mpl-toolbar';\n",
              "    this.root.appendChild(toolbar);\n",
              "\n",
              "    function on_click_closure(name) {\n",
              "        return function (_event) {\n",
              "            return fig.toolbar_button_onclick(name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    function on_mouseover_closure(tooltip) {\n",
              "        return function (event) {\n",
              "            if (!event.currentTarget.disabled) {\n",
              "                return fig.toolbar_button_onmouseover(tooltip);\n",
              "            }\n",
              "        };\n",
              "    }\n",
              "\n",
              "    fig.buttons = {};\n",
              "    var buttonGroup = document.createElement('div');\n",
              "    buttonGroup.classList = 'mpl-button-group';\n",
              "    for (var toolbar_ind in mpl.toolbar_items) {\n",
              "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
              "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
              "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
              "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
              "\n",
              "        if (!name) {\n",
              "            /* Instead of a spacer, we start a new button group. */\n",
              "            if (buttonGroup.hasChildNodes()) {\n",
              "                toolbar.appendChild(buttonGroup);\n",
              "            }\n",
              "            buttonGroup = document.createElement('div');\n",
              "            buttonGroup.classList = 'mpl-button-group';\n",
              "            continue;\n",
              "        }\n",
              "\n",
              "        var button = (fig.buttons[name] = document.createElement('button'));\n",
              "        button.classList = 'mpl-widget';\n",
              "        button.setAttribute('role', 'button');\n",
              "        button.setAttribute('aria-disabled', 'false');\n",
              "        button.addEventListener('click', on_click_closure(method_name));\n",
              "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
              "\n",
              "        var icon_img = document.createElement('img');\n",
              "        icon_img.src = '_images/' + image + '.png';\n",
              "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
              "        icon_img.alt = tooltip;\n",
              "        button.appendChild(icon_img);\n",
              "\n",
              "        buttonGroup.appendChild(button);\n",
              "    }\n",
              "\n",
              "    if (buttonGroup.hasChildNodes()) {\n",
              "        toolbar.appendChild(buttonGroup);\n",
              "    }\n",
              "\n",
              "    var fmt_picker = document.createElement('select');\n",
              "    fmt_picker.classList = 'mpl-widget';\n",
              "    toolbar.appendChild(fmt_picker);\n",
              "    this.format_dropdown = fmt_picker;\n",
              "\n",
              "    for (var ind in mpl.extensions) {\n",
              "        var fmt = mpl.extensions[ind];\n",
              "        var option = document.createElement('option');\n",
              "        option.selected = fmt === mpl.default_extension;\n",
              "        option.innerHTML = fmt;\n",
              "        fmt_picker.appendChild(option);\n",
              "    }\n",
              "\n",
              "    var status_bar = document.createElement('span');\n",
              "    status_bar.classList = 'mpl-message';\n",
              "    toolbar.appendChild(status_bar);\n",
              "    this.message = status_bar;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
              "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
              "    // which will in turn request a refresh of the image.\n",
              "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.send_message = function (type, properties) {\n",
              "    properties['type'] = type;\n",
              "    properties['figure_id'] = this.id;\n",
              "    this.ws.send(JSON.stringify(properties));\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.send_draw_message = function () {\n",
              "    if (!this.waiting) {\n",
              "        this.waiting = true;\n",
              "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
              "    var format_dropdown = fig.format_dropdown;\n",
              "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
              "    fig.ondownload(fig, format);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
              "    var size = msg['size'];\n",
              "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
              "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
              "        fig.send_message('refresh', {});\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
              "    var x0 = msg['x0'] / fig.ratio;\n",
              "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
              "    var x1 = msg['x1'] / fig.ratio;\n",
              "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
              "    x0 = Math.floor(x0) + 0.5;\n",
              "    y0 = Math.floor(y0) + 0.5;\n",
              "    x1 = Math.floor(x1) + 0.5;\n",
              "    y1 = Math.floor(y1) + 0.5;\n",
              "    var min_x = Math.min(x0, x1);\n",
              "    var min_y = Math.min(y0, y1);\n",
              "    var width = Math.abs(x1 - x0);\n",
              "    var height = Math.abs(y1 - y0);\n",
              "\n",
              "    fig.rubberband_context.clearRect(\n",
              "        0,\n",
              "        0,\n",
              "        fig.canvas.width / fig.ratio,\n",
              "        fig.canvas.height / fig.ratio\n",
              "    );\n",
              "\n",
              "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
              "    // Updates the figure title.\n",
              "    fig.header.textContent = msg['label'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
              "    var cursor = msg['cursor'];\n",
              "    switch (cursor) {\n",
              "        case 0:\n",
              "            cursor = 'pointer';\n",
              "            break;\n",
              "        case 1:\n",
              "            cursor = 'default';\n",
              "            break;\n",
              "        case 2:\n",
              "            cursor = 'crosshair';\n",
              "            break;\n",
              "        case 3:\n",
              "            cursor = 'move';\n",
              "            break;\n",
              "    }\n",
              "    fig.rubberband_canvas.style.cursor = cursor;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
              "    fig.message.textContent = msg['message'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
              "    // Request the server to send over a new figure.\n",
              "    fig.send_draw_message();\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
              "    fig.image_mode = msg['mode'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
              "    for (var key in msg) {\n",
              "        if (!(key in fig.buttons)) {\n",
              "            continue;\n",
              "        }\n",
              "        fig.buttons[key].disabled = !msg[key];\n",
              "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
              "    if (msg['mode'] === 'PAN') {\n",
              "        fig.buttons['Pan'].classList.add('active');\n",
              "        fig.buttons['Zoom'].classList.remove('active');\n",
              "    } else if (msg['mode'] === 'ZOOM') {\n",
              "        fig.buttons['Pan'].classList.remove('active');\n",
              "        fig.buttons['Zoom'].classList.add('active');\n",
              "    } else {\n",
              "        fig.buttons['Pan'].classList.remove('active');\n",
              "        fig.buttons['Zoom'].classList.remove('active');\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function () {\n",
              "    // Called whenever the canvas gets updated.\n",
              "    this.send_message('ack', {});\n",
              "};\n",
              "\n",
              "// A function to construct a web socket function for onmessage handling.\n",
              "// Called in the figure constructor.\n",
              "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
              "    return function socket_on_message(evt) {\n",
              "        if (evt.data instanceof Blob) {\n",
              "            /* FIXME: We get \"Resource interpreted as Image but\n",
              "             * transferred with MIME type text/plain:\" errors on\n",
              "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
              "             * to be part of the websocket stream */\n",
              "            evt.data.type = 'image/png';\n",
              "\n",
              "            /* Free the memory for the previous frames */\n",
              "            if (fig.imageObj.src) {\n",
              "                (window.URL || window.webkitURL).revokeObjectURL(\n",
              "                    fig.imageObj.src\n",
              "                );\n",
              "            }\n",
              "\n",
              "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
              "                evt.data\n",
              "            );\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        } else if (\n",
              "            typeof evt.data === 'string' &&\n",
              "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
              "        ) {\n",
              "            fig.imageObj.src = evt.data;\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        }\n",
              "\n",
              "        var msg = JSON.parse(evt.data);\n",
              "        var msg_type = msg['type'];\n",
              "\n",
              "        // Call the  \"handle_{type}\" callback, which takes\n",
              "        // the figure and JSON message as its only arguments.\n",
              "        try {\n",
              "            var callback = fig['handle_' + msg_type];\n",
              "        } catch (e) {\n",
              "            console.log(\n",
              "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
              "                msg\n",
              "            );\n",
              "            return;\n",
              "        }\n",
              "\n",
              "        if (callback) {\n",
              "            try {\n",
              "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
              "                callback(fig, msg);\n",
              "            } catch (e) {\n",
              "                console.log(\n",
              "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
              "                    e,\n",
              "                    e.stack,\n",
              "                    msg\n",
              "                );\n",
              "            }\n",
              "        }\n",
              "    };\n",
              "};\n",
              "\n",
              "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
              "mpl.findpos = function (e) {\n",
              "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
              "    var targ;\n",
              "    if (!e) {\n",
              "        e = window.event;\n",
              "    }\n",
              "    if (e.target) {\n",
              "        targ = e.target;\n",
              "    } else if (e.srcElement) {\n",
              "        targ = e.srcElement;\n",
              "    }\n",
              "    if (targ.nodeType === 3) {\n",
              "        // defeat Safari bug\n",
              "        targ = targ.parentNode;\n",
              "    }\n",
              "\n",
              "    // pageX,Y are the mouse positions relative to the document\n",
              "    var boundingRect = targ.getBoundingClientRect();\n",
              "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
              "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
              "\n",
              "    return { x: x, y: y };\n",
              "};\n",
              "\n",
              "/*\n",
              " * return a copy of an object with only non-object keys\n",
              " * we need this to avoid circular references\n",
              " * http://stackoverflow.com/a/24161582/3208463\n",
              " */\n",
              "function simpleKeys(original) {\n",
              "    return Object.keys(original).reduce(function (obj, key) {\n",
              "        if (typeof original[key] !== 'object') {\n",
              "            obj[key] = original[key];\n",
              "        }\n",
              "        return obj;\n",
              "    }, {});\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.mouse_event = function (event, name) {\n",
              "    var canvas_pos = mpl.findpos(event);\n",
              "\n",
              "    if (name === 'button_press') {\n",
              "        this.canvas.focus();\n",
              "        this.canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    var x = canvas_pos.x * this.ratio;\n",
              "    var y = canvas_pos.y * this.ratio;\n",
              "\n",
              "    this.send_message(name, {\n",
              "        x: x,\n",
              "        y: y,\n",
              "        button: event.button,\n",
              "        step: event.step,\n",
              "        guiEvent: simpleKeys(event),\n",
              "    });\n",
              "\n",
              "    /* This prevents the web browser from automatically changing to\n",
              "     * the text insertion cursor when the button is pressed.  We want\n",
              "     * to control all of the cursor setting manually through the\n",
              "     * 'cursor' event from matplotlib */\n",
              "    event.preventDefault();\n",
              "    return false;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
              "    // Handle any extra behaviour associated with a key event\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.key_event = function (event, name) {\n",
              "    // Prevent repeat events\n",
              "    if (name === 'key_press') {\n",
              "        if (event.which === this._key) {\n",
              "            return;\n",
              "        } else {\n",
              "            this._key = event.which;\n",
              "        }\n",
              "    }\n",
              "    if (name === 'key_release') {\n",
              "        this._key = null;\n",
              "    }\n",
              "\n",
              "    var value = '';\n",
              "    if (event.ctrlKey && event.which !== 17) {\n",
              "        value += 'ctrl+';\n",
              "    }\n",
              "    if (event.altKey && event.which !== 18) {\n",
              "        value += 'alt+';\n",
              "    }\n",
              "    if (event.shiftKey && event.which !== 16) {\n",
              "        value += 'shift+';\n",
              "    }\n",
              "\n",
              "    value += 'k';\n",
              "    value += event.which.toString();\n",
              "\n",
              "    this._key_event_extra(event, name);\n",
              "\n",
              "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
              "    return false;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
              "    if (name === 'download') {\n",
              "        this.handle_save(this, null);\n",
              "    } else {\n",
              "        this.send_message('toolbar_button', { name: name });\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
              "    this.message.textContent = tooltip;\n",
              "};\n",
              "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
              "\n",
              "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
              "\n",
              "mpl.default_extension = \"png\";/* global mpl */\n",
              "\n",
              "var comm_websocket_adapter = function (comm) {\n",
              "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
              "    // object with the appropriate methods. Currently this is a non binary\n",
              "    // socket, so there is still some room for performance tuning.\n",
              "    var ws = {};\n",
              "\n",
              "    ws.close = function () {\n",
              "        comm.close();\n",
              "    };\n",
              "    ws.send = function (m) {\n",
              "        //console.log('sending', m);\n",
              "        comm.send(m);\n",
              "    };\n",
              "    // Register the callback with on_msg.\n",
              "    comm.on_msg(function (msg) {\n",
              "        //console.log('receiving', msg['content']['data'], msg);\n",
              "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
              "        ws.onmessage(msg['content']['data']);\n",
              "    });\n",
              "    return ws;\n",
              "};\n",
              "\n",
              "mpl.mpl_figure_comm = function (comm, msg) {\n",
              "    // This is the function which gets called when the mpl process\n",
              "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
              "\n",
              "    var id = msg.content.data.id;\n",
              "    // Get hold of the div created by the display call when the Comm\n",
              "    // socket was opened in Python.\n",
              "    var element = document.getElementById(id);\n",
              "    var ws_proxy = comm_websocket_adapter(comm);\n",
              "\n",
              "    function ondownload(figure, _format) {\n",
              "        window.open(figure.canvas.toDataURL());\n",
              "    }\n",
              "\n",
              "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
              "\n",
              "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
              "    // web socket which is closed, not our websocket->open comm proxy.\n",
              "    ws_proxy.onopen();\n",
              "\n",
              "    fig.parent_element = element;\n",
              "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
              "    if (!fig.cell_info) {\n",
              "        console.error('Failed to find cell for figure', id, fig);\n",
              "        return;\n",
              "    }\n",
              "    fig.cell_info[0].output_area.element.one(\n",
              "        'cleared',\n",
              "        { fig: fig },\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
              "    var width = fig.canvas.width / fig.ratio;\n",
              "    fig.cell_info[0].output_area.element.off(\n",
              "        'cleared',\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "\n",
              "    // Update the output cell to use the data from the current canvas.\n",
              "    fig.push_to_output();\n",
              "    var dataURL = fig.canvas.toDataURL();\n",
              "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
              "    // the notebook keyboard shortcuts fail.\n",
              "    IPython.keyboard_manager.enable();\n",
              "    fig.parent_element.innerHTML =\n",
              "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
              "    fig.close_ws(fig, msg);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
              "    fig.send_message('closing', msg);\n",
              "    // fig.ws.close()\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
              "    // Turn the data on the canvas into data in the output cell.\n",
              "    var width = this.canvas.width / this.ratio;\n",
              "    var dataURL = this.canvas.toDataURL();\n",
              "    this.cell_info[1]['text/html'] =\n",
              "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function () {\n",
              "    // Tell IPython that the notebook contents must change.\n",
              "    IPython.notebook.set_dirty(true);\n",
              "    this.send_message('ack', {});\n",
              "    var fig = this;\n",
              "    // Wait a second, then push the new image to the DOM so\n",
              "    // that it is saved nicely (might be nice to debounce this).\n",
              "    setTimeout(function () {\n",
              "        fig.push_to_output();\n",
              "    }, 1000);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var toolbar = document.createElement('div');\n",
              "    toolbar.classList = 'btn-toolbar';\n",
              "    this.root.appendChild(toolbar);\n",
              "\n",
              "    function on_click_closure(name) {\n",
              "        return function (_event) {\n",
              "            return fig.toolbar_button_onclick(name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    function on_mouseover_closure(tooltip) {\n",
              "        return function (event) {\n",
              "            if (!event.currentTarget.disabled) {\n",
              "                return fig.toolbar_button_onmouseover(tooltip);\n",
              "            }\n",
              "        };\n",
              "    }\n",
              "\n",
              "    fig.buttons = {};\n",
              "    var buttonGroup = document.createElement('div');\n",
              "    buttonGroup.classList = 'btn-group';\n",
              "    var button;\n",
              "    for (var toolbar_ind in mpl.toolbar_items) {\n",
              "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
              "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
              "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
              "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
              "\n",
              "        if (!name) {\n",
              "            /* Instead of a spacer, we start a new button group. */\n",
              "            if (buttonGroup.hasChildNodes()) {\n",
              "                toolbar.appendChild(buttonGroup);\n",
              "            }\n",
              "            buttonGroup = document.createElement('div');\n",
              "            buttonGroup.classList = 'btn-group';\n",
              "            continue;\n",
              "        }\n",
              "\n",
              "        button = fig.buttons[name] = document.createElement('button');\n",
              "        button.classList = 'btn btn-default';\n",
              "        button.href = '#';\n",
              "        button.title = name;\n",
              "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
              "        button.addEventListener('click', on_click_closure(method_name));\n",
              "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
              "        buttonGroup.appendChild(button);\n",
              "    }\n",
              "\n",
              "    if (buttonGroup.hasChildNodes()) {\n",
              "        toolbar.appendChild(buttonGroup);\n",
              "    }\n",
              "\n",
              "    // Add the status bar.\n",
              "    var status_bar = document.createElement('span');\n",
              "    status_bar.classList = 'mpl-message pull-right';\n",
              "    toolbar.appendChild(status_bar);\n",
              "    this.message = status_bar;\n",
              "\n",
              "    // Add the close button to the window.\n",
              "    var buttongrp = document.createElement('div');\n",
              "    buttongrp.classList = 'btn-group inline pull-right';\n",
              "    button = document.createElement('button');\n",
              "    button.classList = 'btn btn-mini btn-primary';\n",
              "    button.href = '#';\n",
              "    button.title = 'Stop Interaction';\n",
              "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
              "    button.addEventListener('click', function (_evt) {\n",
              "        fig.handle_close(fig, {});\n",
              "    });\n",
              "    button.addEventListener(\n",
              "        'mouseover',\n",
              "        on_mouseover_closure('Stop Interaction')\n",
              "    );\n",
              "    buttongrp.appendChild(button);\n",
              "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
              "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
              "    var fig = event.data.fig;\n",
              "    fig.close_ws(fig, {});\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function (el) {\n",
              "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
              "    // this is important to make the div 'focusable\n",
              "    el.setAttribute('tabindex', 0);\n",
              "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
              "    // off when our div gets focus\n",
              "\n",
              "    // location in version 3\n",
              "    if (IPython.notebook.keyboard_manager) {\n",
              "        IPython.notebook.keyboard_manager.register_events(el);\n",
              "    } else {\n",
              "        // location in version 2\n",
              "        IPython.keyboard_manager.register_events(el);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
              "    var manager = IPython.notebook.keyboard_manager;\n",
              "    if (!manager) {\n",
              "        manager = IPython.keyboard_manager;\n",
              "    }\n",
              "\n",
              "    // Check for shift+enter\n",
              "    if (event.shiftKey && event.which === 13) {\n",
              "        this.canvas_div.blur();\n",
              "        // select the cell after this one\n",
              "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
              "        IPython.notebook.select(index + 1);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
              "    fig.ondownload(fig, null);\n",
              "};\n",
              "\n",
              "mpl.find_output_cell = function (html_output) {\n",
              "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
              "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
              "    // IPython event is triggered only after the cells have been serialised, which for\n",
              "    // our purposes (turning an active figure into a static one), is too late.\n",
              "    var cells = IPython.notebook.get_cells();\n",
              "    var ncells = cells.length;\n",
              "    for (var i = 0; i < ncells; i++) {\n",
              "        var cell = cells[i];\n",
              "        if (cell.cell_type === 'code') {\n",
              "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
              "                var data = cell.output_area.outputs[j];\n",
              "                if (data.data) {\n",
              "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
              "                    data = data.data;\n",
              "                }\n",
              "                if (data['text/html'] === html_output) {\n",
              "                    return [cell, data, j];\n",
              "                }\n",
              "            }\n",
              "        }\n",
              "    }\n",
              "};\n",
              "\n",
              "// Register the function which deals with the matplotlib target/channel.\n",
              "// The kernel may be null if the page has been refreshed.\n",
              "if (IPython.notebook.kernel !== null) {\n",
              "    IPython.notebook.kernel.comm_manager.register_target(\n",
              "        'matplotlib',\n",
              "        mpl.mpl_figure_comm\n",
              "    );\n",
              "}\n"
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
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          "output_type": "display_data"
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            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "display_pca_scatterplot(wv, sample=300)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dL9eE7Hu_3Dp"
      },
      "source": [
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lhzaTWQ9_3Dp"
      },
      "source": [
        "### Exercise\n",
        "\n",
        "1. Try the same analogy experiments and visualizations with another pre-trained model from Gensim, e.g. GloVe Twitter or Word2Vec Google News.\n",
        "2. Train your own model following the steps detailed here: https://radimrehurek.com/gensim/auto_examples/tutorials/run_word2vec.html#training-your-own-model. You could use, for example, the Brown or Reuters corpora from NLTK. Do the pre-processing which you deem useful."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "DaQOZhk8_3Dp"
      },
      "outputs": [],
      "source": [
        "# your code here"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.5"
    },
    "toc": {
      "base_numbering": 1,
      "nav_menu": {},
      "number_sections": true,
      "sideBar": true,
      "skip_h1_title": false,
      "title_cell": "Table of Contents",
      "title_sidebar": "Contents",
      "toc_cell": false,
      "toc_position": {},
      "toc_section_display": true,
      "toc_window_display": true
    },
    "colab": {
      "name": "5_WordEmbeddings.ipynb",
      "provenance": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}