Small updates for recent versions of sklearn & seaborn

01-PCA.ipynb

@@ -337,7 +337,7 @@
    "outputs": [],
    "source": [
     "# fancier plot with seaborn : https://seaborn.pydata.org/\n",
-    "import seaborn.apionly as sns\n",
+    "import seaborn as sns\n",
     "sns.set_style('whitegrid')\n",
     "\n",
     "sns.jointplot('Shot.put', 'High.jump', data = my_data, \n",
@@ -610,7 +610,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.8.3"
   }
  },
  "nbformat": 4,

02-FeatureProcessing.ipynb

@@ -497,7 +497,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.8.3"
   }
  },
  "nbformat": 4,

03-linear-and-logistic-regression.ipynb

@@ -93,8 +93,8 @@
    "outputs": [],
    "source": [
     "# set up folds for cross_validation\n",
-    "from sklearn import cross_validation\n",
-    "folds_regr = cross_validation.KFold(y_regr.size, n_folds=10, shuffle=True)"
+    "from sklearn import model_selection\n",
+    "folds_regr = model_selection.KFold(y_regr.size, n_folds=10, shuffle=True)"
    ]
   },
   {
@@ -233,8 +233,8 @@
    "outputs": [],
    "source": [
     "# Set up folds for cross_validation\n",
-    "from sklearn import cross_validation\n",
-    "folds_clf = cross_validation.StratifiedKFold(y_clf, n_folds=10, shuffle=True)"
+    "from sklearn import model_selection\n",
+    "folds_clf = model_selection.StratifiedKFold(y_clf, n_folds=10, shuffle=True)"
    ]
   },
   {

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2019 Chloe-Agathe Azencott
+Copyright (c) 2019 Chloe-Agathe Azencott, N. Varoquaux
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -4,6 +4,7 @@ https://www.hpc-ai.mines-paristech.fr/
 
 ## Requirements
 The labs were developed for Python3. All required packages are part of the [Anaconda platform](https://www.anaconda.com/download/) so you can simply install Anaconda3 on your machine. If you'd rather install just the required packages with pip, that is also possible. The labs were developed for Python 3.4.3, with the following libraries:
+
 * numpy 1.16.5
 * scipy 1.2.2
 * matplotlib 2.2.4