Merge pull request #33 from appliedAI-Initiative/hide_solutions_and_m…

…inor_fixes fix formulas in evt and update imges
aai-institute · Dec 14, 2022 · b769296 · b769296
2 parents 635afdc + 7a139ee
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diff --git a/README.md b/README.md
@@ -39,6 +39,7 @@ extensions.
 To configure everything, activate a conda env and run
 ```bash
 conda install -c conda-forge notebook rise jupyter_contrib_nbextensions jupyter_nbextensions_configurator
+conda install -c conda-forge ffmpeg
 python ./configure_spellcheck_dict.py
 jupyter nbextension enable spellchecker/main
 jupyter nbextension enable equation-numbering/main
@@ -61,6 +62,5 @@ pip install -r requirements.txt
 pip install -e src
 ```
 
-### HTML Animations
-Some notebook cells use HTML animations. If you encounter an error 'Requested MovieWriter (ffmpeg) not available' try following the advices given 
-[here](https://suryadayn.medium.com/error-requested-moviewriter-ffmpeg-not-available-easy-fix-9d1890a487d3).
+## References
+You can find the main references for the workshop [here](docs/references.md).
diff --git a/docs/references.md b/docs/references.md
@@ -26,227 +26,12 @@
 
 
 # Deep Learning
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-](https://arxiv.org/pdf/2007.02500.pdf)
+[A review of DL for anomaly detection](https://arxiv.org/pdf/2007.02500.pdf)
 - Recent successes in anomaly detection through modern deep learning methods such as generative adversarial 
   networks have attracted much attention lately.
-- This article provides a sound and relatively up-to-date review over the available methods. 
+- This article provides a sound and relatively up-to-date review over the available methods.
+
+# Extreme value Theory
+[An introduction to statistical modelling of EVT](https://link.springer.com/book/10.1007/978-1-4471-3675-0)
+- Book that covers all the basics with an application driven (statistical) mindset
 
diff --git a/notebooks/anomaly_detection_approaches.ipynb b/notebooks/anomaly_detection_approaches.ipynb
@@ -186,7 +186,7 @@
    "execution_count": null,
    "id": "10d29d49",
    "metadata": {
-    "hideCode": true,
+    "hideCode": false,
     "pycharm": {
      "name": "#%%\n"
     }
@@ -257,7 +257,7 @@
    "execution_count": null,
    "id": "89e5ef25",
    "metadata": {
-    "hideCode": true,
+    "hideCode": false,
     "pycharm": {
      "name": "#%%\n"
     },
@@ -516,21 +516,18 @@
     "### Solution"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "f81d6a1e",
-   "metadata": {},
-   "source": [
-    "When data are highly in-homogeneous, like in this case, it is often beneficial to rescale them before applying any anomaly detection or clustering technique."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "b336ebbd",
-   "metadata": {},
+   "metadata": {
+    "hideCode": false,
+    "hidePrompt": false
+   },
    "outputs": [],
    "source": [
+    "# When data are highly in-homogeneous, like in this case, it is often beneficial \n",
+    "# to rescale them before applying any anomaly detection or clustering technique.\n",
     "scaler = MinMaxScaler()\n",
     "X_train_rescaled = scaler.fit_transform(X_train)"
    ]
@@ -539,7 +536,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "0159cf66",
-   "metadata": {},
+   "metadata": {
+    "hideCode": false
+   },
    "outputs": [],
    "source": [
     "param_space = {\n",
@@ -553,7 +552,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "c6217804",
-   "metadata": {},
+   "metadata": {
+    "hideCode": false
+   },
    "outputs": [],
    "source": [
     "print('Best parameters:')\n",
@@ -809,7 +810,7 @@
    "execution_count": null,
    "id": "b6861d26",
    "metadata": {
-    "hideCode": true,
+    "hideCode": false,
     "pycharm": {
      "name": "#%%\n"
     },
@@ -1530,6 +1531,7 @@
    "execution_count": null,
    "id": "920afcf1",
    "metadata": {
+    "hideCode": false,
     "pycharm": {
      "name": "#%%\n"
     },
@@ -2403,7 +2405,7 @@
   }
  ],
  "metadata": {
-  "celltoolbar": "Slideshow",
+  "celltoolbar": "Hide code",
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",