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This session is dedicated to an introduction of (artificial) neural networks and discusses a basic network architecture for classification, the (multilayer) feedforward neural network (FNN), and an unsupervised network, the autoencoder (AE), which can be used in a classification setting.

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Classification and Regression 4

Open In Colab

This session is dedicated to an introduction of (artificial) neural networks and discusses a basic network architecture for classification, the (multilayer) Feedforward Neural Network (FNN), and an unsupervised network, the AutoEncoder (AE), which can be used in a classification setting.

For feature importance, you can use tools we used in other BIDS tutorials, or another package called shap, install via:

conda install -c conda-forge shap # alternatively do pip install shap

Have a play around with some toy data and neural networks in a browser: playground

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This session is dedicated to an introduction of (artificial) neural networks and discusses a basic network architecture for classification, the (multilayer) feedforward neural network (FNN), and an unsupervised network, the autoencoder (AE), which can be used in a classification setting.

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