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CMS Machine Learning Hands-on Advanced Tutorial Session (HATS)

Setup

Purdue Analysis Facility
Vanderbilt JupyterHub
LPC
Setup Libraries

Tutorials

1. Loading Datasets
2. Boosted decision trees with xgboost
3. Dense networks
4. Convolutional Neural Networks for Jet-Images
5. Graph Neural Network (GNN) with PyTorch Geometric
6. Variational Autoencoders with Keras and MNIST
8. Generative Adversarial Networks with Keras and MNIST

Repository
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Dense networks

3. Dense networks#

We train dense neural networks in Keras and PyTorch, and provide an example of tuning the hyperparameters using Bayesian optimization.

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2. Boosted decision trees with xgboost

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3.1. Dense neural network with Keras

By Raghav Kansal, on behalf of the LPC

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