Lab Work @ Deep Learning

at CentraleSupélec 👨🏻‍💻

Note

The main aim of this repository is to keep track of the work we have done in Deep Learning (DL) lab at CentraleSupélec. It contains the labs, the setup, and the main topics covered in the course.

Table of contents

• Introduction
• About the course
  • Main Topics
• Labs
• Setup

1. Introduction

The main goal of this course is to present the basics of Deep Learning and some of its applications. It is based on several widely known courses that has proven effective such as the Deep Learning Book and Dive into Deep Learning website.

We will take interest in various domains of Deep Learning such as Computer Vision, Generative Models, and Natural Language Processing, To put into application what you will learn, various practical sessions will be performed along with a small project on a specific task.

2. About the course

At the end of this course you will be able to:

• Perform the training of Deep Learning models as well as evaluate their performance
• Discuss and provide solutions to various tasks in Computer Vision, Generative Models, Natural Language Processing etc

2.1. Main Topics

• Introduction + Machine Learning Basics + Deep Neural Networks: fundamentals
• Deep Neural Networks: Optimization and Regularization
• Convolutional Neural Networks
• Generative Models
• Recurrent Neural Networks, attention and transformers
• Natural Language Processing

3. Labs

No.	Lab
01	Manual implementation of Neural Networks and basics of Pytorch
02	Convolutional Neural Networks and Finetuning
03	Generative Models for images
04	Action classification for videos
05	Natural Language Processing with data processing and finetuning

4. Setup

Before starting, you may have to create new enviornment for the lab. Kindly, checkout the documentation for creating an new environment.

If you want to follow along with the lab exercises, make sure to clone and cd to the relevant lab's directory:

git clone https://github.com/mohammadzainabbas/Deep-Learning-Lab-CS.git
cd Deep-Learning-Lab-CS/src/<lab-of-your-choice>

Tip

For e.g: if you want to practice lab #1, then you should do:

cd Deep-Learning-Lab-CS/src/multi-layer-perceptron