Small fixes here and there

03-linear-and-logistic-regression.ipynb

@@ -177,9 +177,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Load the classification task data\n",
@@ -517,7 +515,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.8.3"
   }
  },
  "nbformat": 4,

README.md

@@ -22,13 +22,7 @@ To __check your installation__, try launching Jupyter (e.g. by typing `jupyter n
 ## Program
 * Lab 1: [Principal Component Analysis](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/01-PCA.ipynb) (1h)
 * Lab 2: [Data normalization](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/02-FeatureProcessing.ipynb) (1h)
-* Lab 3: [Introduction to the KaggleInClass project](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/03-ProjectIntro.ipynb) (2h)
-* Lab 4: [Linear and logistic regression](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/04-Linear%20and%20logistic%20regressions.ipynb) (1h) 
-* Lab 5: [Regularized linear regression](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/05-Regularization.ipynb) (1h) 
-* Lab 6: [Nearest neighbors](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/06-NearestNeighbors.ipynb) (1h) 
-* Lab 7: [Trees and Forests](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/07-TreesAndForests.ipynb) (1h) 
-* Lab 8: [Support Vector Machines](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/08-SVM.ipynb) (1h)
-* Lab 9: Work on the project (3h) 
+* Lab 3: [Linear and logistic regression](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/03-Linear%20and%20logistic%20regressions.ipynb) (1h) 
 
 
 ### Acknowledgements