Adding the links to the README

README.md

@@ -1,12 +1,19 @@
 
 [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/NelleV/2022-mines-HPC-AI-TD/HEAD)
 
-# hpc-ai-ml-2019
-This repository holds the computer labs for the Introduction to Machine Learning course of the 2019-2020 HPC-AI MSc 
+# hpc-ai-ml-2022
+
+This repository holds the computer labs for the Introduction to Machine
+Learning course of the 2021-2022 HPC-AI MSc
 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:
+
+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
@@ -15,7 +22,11 @@ The labs were developed for Python3. All required packages are part of the [Anac
 * seaborn 0.9.0
 * sklearn 0.19.2
 
-To __check your installation__, try launching Jupyter (e.g. by typing `jupyter noteboook` in a shell), navigating to where you have downloaded/pulled the first lab (.ipynb file) and opening it. In that notebook (or in a python terminal), you should be able to run 
+To __check your installation__, try launching Jupyter (e.g. by typing `jupyter
+noteboook` in a shell), navigating to where you have downloaded/pulled the
+first lab (.ipynb file) and opening it. In that notebook (or in a python
+terminal), you should be able to run 
+
   ```python
   import sklearn
   import pandas
@@ -29,6 +40,8 @@ To __check your installation__, try launching Jupyter (e.g. by typing `jupyter n
 * Lab 3: [Cross validation & features](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/03-ProjectIntro.ipynb) 
 * 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 models](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/05-Regularization.ipynb) (1h) 
+* Lab 6: [Trees and Forests](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/06-TreesAndForests.ipynb) 
+* Lab 7: [k-NN](https://github.com/NelleV/2022-mines-HPC-AI-TD/blob/master/07-NearestNeighbors.ipynb) 
 
 
 ### Acknowledgements