diff --git a/03 - Classification.ipynb b/03 - Classification.ipynb index 5795a9b..36d4cad 100644 --- a/03 - Classification.ipynb +++ b/03 - Classification.ipynb @@ -688,7 +688,7 @@ }, "outputs": [], "source": [ - "penguin_classes = ['Amelie', 'Gentoo', 'Chinstrap']\n", + "penguin_classes = ['Adelie', 'Gentoo', 'Chinstrap']\n", "print(sample.columns[0:5].values, 'SpeciesName')\n", "for index, row in penguins.sample(10).iterrows():\n", " print('[',row[0], row[1], row[2], row[3], int(row[4]),']',penguin_classes[int(row[4])])" @@ -1204,4 +1204,4 @@ }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/05a - Deep Neural Networks (PyTorch).ipynb b/05a - Deep Neural Networks (PyTorch).ipynb index 084204c..565db70 100644 --- a/05a - Deep Neural Networks (PyTorch).ipynb +++ b/05a - Deep Neural Networks (PyTorch).ipynb @@ -65,7 +65,7 @@ }, "outputs": [], "source": [ - "penguin_classes = ['Amelie', 'Gentoo', 'Chinstrap']\n", + "penguin_classes = ['Adelie', 'Gentoo', 'Chinstrap']\n", "print(sample.columns[0:5].values, 'SpeciesName')\n", "for index, row in penguins.sample(10).iterrows():\n", " print('[',row[0], row[1], row[2],row[3], int(row[4]), ']',penguin_classes[int(row[-1])])" @@ -109,7 +109,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The *features* are the measurements for each penguin observation, and the *label* is a numeric value that indicates the species of penguin that the observation represents (Amelie, Gentoo, or Chinstrap).\n", + "The *features* are the measurements for each penguin observation, and the *label* is a numeric value that indicates the species of penguin that the observation represents (Adelie, Gentoo, or Chinstrap).\n", "\n", "## Install and import the PyTorch libraries\n", "\n", diff --git a/05a - Deep Neural Networks (TensorFlow).ipynb b/05a - Deep Neural Networks (TensorFlow).ipynb index c7fe0b7..baae4cd 100644 --- a/05a - Deep Neural Networks (TensorFlow).ipynb +++ b/05a - Deep Neural Networks (TensorFlow).ipynb @@ -65,7 +65,7 @@ }, "outputs": [], "source": [ - "penguin_classes = ['Amelie', 'Gentoo', 'Chinstrap']\n", + "penguin_classes = ['Adelie', 'Gentoo', 'Chinstrap']\n", "print(sample.columns[0:5].values, 'SpeciesName')\n", "for index, row in penguins.sample(10).iterrows():\n", " print('[',row[0], row[1], row[2],row[3], int(row[4]), ']',penguin_classes[int(row[-1])])" @@ -109,7 +109,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The *features* are the measurements for each penguin observation, and the *label* is a numeric value that indicates the species of penguin that the observation represents (Amelie, Gentoo, or Chinstrap).\n", + "The *features* are the measurements for each penguin observation, and the *label* is a numeric value that indicates the species of penguin that the observation represents (Adelie, Gentoo, or Chinstrap).\n", "\n", "## Install and import TensorFlow libraries\n", "\n",