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Name and Link | ML Technologies | Scientific Field | ML Tools | Comments |
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Btagging in CMS (templated version) | CNN, LSTM | High Energy Physics | Keras + Tensorflow | Realistic application |
LHCb Masterclass, with Keras | DE, MLP | High Energy Physics | ROOT + Keras + TF | Introductory tutorial |
MNIST in a C header | MLP | Keras | Free-styling tutorial | |
CNN, RNN, GNN | High Energy Physics | PyTorch | Package use examples | |
INFERNO: Inference-Aware Neural Optimisation | NN | High Energy Physics | Keras + Tensorflow | Technique application example |
An introduction to classification with CMS data | Fisher, BDT, MLP | High Energy Physics | Scikit-learn, TF2 | Tutorials for Master Students |
7. Virgo Autoencoder tutorial | Autoencoder | General Relativity | Python Keras | Tutorial for student |
Distributed training of neural networks with Apache Spark | DNN | High Energy Physics | Spark + BigDL | Tutorial |
FTS log analysis with NLP | NLP | High Energy Physics, Computing | Word2Vec + Rake + sklearn | |
Image Inpainting tutorial: how to digitally restore damaged images | CNN U-Net | Applied Physics | Keras + Sci-kit image, PIL, OpenCV, matplotlib | Tutorial |
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