Commit 9d377b6c authored by Florent Chatelain's avatar Florent Chatelain
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lab

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......@@ -14,17 +14,3 @@ See the notebooks in the [6_linear_models_ridge](https://gricad-gitlab.univ-gren
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*-->
## Part II: Lasso (L1) regularization
See the notebooks in the [6bis_linear_models_lasso_logistic](https://gricad-gitlab.univ-grenoble-alpes.fr/ai-courses/autonomous_systems_ml/-/blob/master/notebooks/6bis_linear_models_lasso_logistic/) folder:
1. Experiment the effect of lasso (L1) regularization [`N1_L1_regularization.ipynb`](https://gricad-gitlab.univ-grenoble-alpes.fr/ai-courses/autonomous_systems_ml/-/blob/master/notebooks/6bis_linear_models_lasso_logistic/N1_L1_regularization.ipynb)
2. Perform Lasso penalized Logistic Regression, and greedy variable selection procedures, to model the risk of coronary heart disease based on clinical data [`N2_LR_heart_diseases_SA.ipynb`](https://gricad-gitlab.univ-grenoble-alpes.fr/ai-courses/autonomous_systems_ml/-/blob/master/notebooks/6bis_linear_models_lasso_logistic/N2_LR_heart_diseases_SA.ipynb)
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*
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