Commit cbae5ce2 authored by Florent Chatelain's avatar Florent Chatelain
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fix lab5 nb links

parent 3db6ca76
# Linear models: 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:
See the notebooks in the [7_linear_models_lasso_logistic](https://gricad-gitlab.univ-grenoble-alpes.fr/ai-courses/autonomous_systems_ml/-/blob/master/notebooks/7_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)
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/7_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)
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/7_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)
[`N3_lasso_curse_dimensionality.ipynb`](https://gricad-gitlab.univ-grenoble-alpes.fr/ai-courses/autonomous_systems_ml/-/blob/master/notebooks/7_linear_models_lasso_logistic/N3_lasso_curse_dimensionality.ipynb)
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*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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