Course materials

M1, ENS Lyon, 2017 - 2018


Machine Learning

TPs

  • TP1: Regression with sklearn and tensorflow   TP1.zip,   TP1_sol.zip.
  • TP3: Image classification with Tensorflow and Keras   TP3.zip,   and birds.zip.
  • TP4: Advanced topics in Deep learning   TP4.zip.
  • TP6: Unsupervised and ensemble methods with Sklearn   TP6.zip.

TDs

  • TD1: Uniform stability   TD1.pdf.
  • TD2: Emsemble methods   TD2.pdf.

Project topics

  1. Deep learning theory (no code): Paper 1, Paper 2, Paper 3.
  2. Reinforcement Learning (no code): Paper 1, Paper 2, Paper 3.
  3. Reinforcement Learning (no code): Paper 1, Paper 2.
  4. Normalizations: Batch norm, Layer norm, Weight norm.
  5. Binarized nets: Binarized net, XNOR net.
  6. GAN: WGAN, Improved WGAN.
  7. GAN: DCGAN, InfoGAN, CycleGAN.
  8. Natural language processing: seq2seq, Glove.
  9. Natural language processing: Sentence classification, Modelling sentences.
  10. Style transfer: Paper 1, Paper 2.
  11. Metric learning: Facenet, Lift structure.
  12. Speech recognition: Deep speech.
  13. Image captioning: Show, attend and tell.
  14. Image segmentation: FCN.
  15. Object detection: Faster R-CNN.
  16. Object detection: Mask R-CNN.
  17. Object detection: YOLO.

Parallel and Distributed Algorithms and Programs

Project

TPs

TDs