# How-To Guide Familiarize with NeMoS modules and learn how to take advantage of the `pynapple` and `scikit-learn` compatibility. :::{dropdown} Additional requirements :color: warning :icon: alert To run the tutorials, you may need to install some additional packages used for plotting and data fetching. You can install all of the required packages with the following command: ``` pip install nemos[examples] ``` ::: ## GLM Fundamentals ::::{grid} 1 2 3 3 :::{grid-item-card}
Save and Load.
```{toctree} :maxdepth: 2 save_and_load.md ``` ::: :::{grid-item-card}
GLM demo.
```{toctree} :maxdepth: 2 plot_02_glm_demo.md ``` ::: :::{grid-item-card}
Population GLM.
```{toctree} :maxdepth: 2 plot_03_population_glm.md ``` ::: :::{grid-item-card}
Coupled GLM.
```{toctree} :maxdepth: 2 raw_history_feature.md ``` ::: :::{grid-item-card}
Confusion Matrix.
```{toctree} :maxdepth: 2 glm_for_classification.md ``` ::: :::{grid-item-card} ```{toctree} :maxdepth: 2 finegrained_regularization.md ``` ::: :::: ## Feature Engineering ::::{grid} 1 2 3 3 :::{grid-item-card} ```{toctree} :maxdepth: 2 handling_composite_bases.md ``` ::: :::{grid-item-card} ```{eval-rst} .. plot:: scripts/basis_figs.py plot_laguerre_basis :show-source-link: False :height: 100px ``` ```{toctree} :maxdepth: 2 define_a_custom_basis.md ``` ::: :::{grid-item-card} ```{eval-rst} .. plot:: scripts/glm_predictors.py plot_categorical_var_design_matrix :show-source-link: False :height: 100px ``` ```{toctree} :maxdepth: 2 categorical_predictors.md ``` ::: :::{grid-item-card} ```{eval-rst} .. plot:: scripts/glm_predictors.py plot_custom_features :show-source-link: False :height: 100px ``` ```{toctree} :maxdepth: 2 custom_predictors.md ``` ::: :::: ## Model Selection and `scikit-learn` Integration ::::{grid} 1 2 3 3 :::{grid-item-card}
NeMoS vs sklearn.
```{toctree} :maxdepth: 2 plot_05_transformer_basis.md ``` ::: :::{grid-item-card}
PyTrees.
```{toctree} :maxdepth: 2 plot_06_sklearn_pipeline_cv_demo.md ``` ::: :::{grid-item-card}
Model Selection.
```{toctree} :maxdepth: 2 variable_selection_zero_basis.md ``` ::: :::{grid-item-card}
Variable selection.
```{toctree} :maxdepth: 2 variable_selection_group_lasso.md ``` ::: :::: ## Performance and Scaling ::::{grid} 1 2 3 3 :::{grid-item-card}
Batching scheme.
```{toctree} :maxdepth: 2 convolve_large_arrays.md ``` ::: :::{grid-item-card}
Batched GLM.
```{toctree} :maxdepth: 2 plot_04_batch_glm.md ``` ::: :::{grid-item-card} ```{toctree} :maxdepth: 2 custom_solvers.md ``` ::: ::::