/m2-bdma-resources

This repository contains practical session resources associated to the Machine Learning course that I taught in 2022.

Primary LanguageJupyter Notebook

Machine Learning M2 BDMA

Introduction

This repository contains practical session resources associated to the Machine Learning course that I taught in 2022.

Classes involved basics of Deep Learning for Computer Vision, Natural Language Processing and Generative Models.

Resources

The files containing the string 'student' are the ones with blanks that students had to fill. The other files are the solutions.

  1. Basics of Deep Learning

Implementation of first Deep Learning networks on the MNIST dataset.

  1. Convolutional Neural Networks

Implementation and usage of CNN on the CIFAR10 dataset.

Usage of data augmentations.

  1. Generative Models

Implementation of a GAN and a VAE to generate new MNIST digits.

  1. RNN

Implementation of RNN to perform action classification.

  1. NLP

Inspired from an HuggingFace tutorial, this practical session focus on finetuning Large Language Models for Q&A task.