lab

labs/lab4_statement.md

@@ -13,4 +13,4 @@ See the notebooks in the [6_linear_models_ridge](https://gricad-gitlab.univ-gren
 3. Apply ridge (L2) regularization for the deconvolution problem [`N3_deconvolution_ridge.ipynb`](https://gricad-gitlab.univ-grenoble-alpes.fr/ai-courses/autonomous_systems_ml/-/blob/master/notebooks/6_linear_models_ridge/N3_deconvolution_ridge.ipynb)
 4. Perform ridge regression for predicting high dimensional NIR biscuits data  [`N4_ridge_NIR_biscuits.ipynb`](https://gricad-gitlab.univ-grenoble-alpes.fr/ai-courses/autonomous_systems_ml/-/blob/master/notebooks/6_linear_models_ridge/N4_ridge_NIR_biscuits.ipynb)
 
-*Note: The two first notebooks are simple interactive demonstrations on the tensorflow playground similar to those made together during the class session.* <!--*They can be skipped during the labwork session*-->
+<!--*Note: The two first notebooks are simple interactive demonstrations on the tensorflow playground similar to those made together during the class session.* They can be skipped during the labwork session*-->

labs/lab5_statement.md

@@ -10,5 +10,5 @@ See the notebooks in the [6bis_linear_models_lasso_logistic](https://gricad-gitl
 
 3. Perform Lasso regression for a high-dimensional sparse model based on the Advertising data set
  [`N3_lasso_curse_dimensionality.ipynb`](https://gricad-gitlab.univ-grenoble-alpes.fr/ai-courses/autonomous_systems_ml/-/blob/master/notebooks/6bis_linear_models_lasso_logistic/N3_lasso_curse_dimensionality.ipynb)
-
-*Note: The first notebook is an interactive demonstration on the tensorflow playground similar to the one made together during the class session.*<!-- *This can be skipped during the labwork session*-->
+<!--
+*Note: The first notebook is an interactive demonstration on the tensorflow playground similar to the one made together during the class session. This can be skipped during the labwork session*-->