ML Course 2024 (Weissman Auditorum Thursdays)

Welcome to the Weizmann practical Deep Learning Course 2024

All communication with the lecturers will be made via SLACK. Join here:

join slack channel

Your lecturers and TAs are
Etienne Dreyer, Nilotpal Kakati, Dmitrii Kobylianskii and Prof Eilam Gross.

The grading system is based on your mandatory homework assignments (10%), a project (<30%), and a take-home assignment (>60%). The exact weight of the project and take-home assignment will be fixed so the class average will not exceed 90.

All lecture slides and tutorial code will be posted below.

Date Lecture Slides
& Video
Tutorial  Slides
& Video
Tutorial 2 Slides
& Video
18/4/2024

Eilam:

Introduction

Lecture 1: Introduction

Etienne:

Python essentials

 

Tutorial 1

Etienne:

NumPy and grad. desc.

Tutorial 1

*2/5/2024

Dmitrii:

Backpropagation

Lecture 2:
Backpropagation

Nilotpal:

pytorch (tut)

notes

notebooks

Nilotpal:

homework 1

Classification

Homework 1

9/5/2024

Eilam:

Convolutional NN

Eilam Lecture 3 CNN

[recording link]

Nilotpal:

CNNs (tut)

notebooks

Dmitrii:

Optimisation,
Regularisation

notebook

*16/5/2024

Etienne:

Autoencoders
(VAE)

slides

Nilotpal:

VAE (tut)

notebooks

Etienne:

transfer learning

homework 2

notebooks

Homework 2

23/5/2024

Eilam:

CNN architectures and RNN

CNN Architectures

CNN Architectures Video 2023

Eilam:

GAN

GAN Lecture

GAN Video 2021

Nilotpal:

DCGAN tutorial

 

**30/5/2024

Nilotpal:

Attention is All You Need
(Transformers)

 

Eilam:

Attenion on Attention

 

Nilotpal:

Attention tutorial

 
**6/6/2024

Eilam:

Detection & Segmentation

 

 

Nilotpal:

UNET

 

 

Dmitrii/Nilotpal:

Homework 3:
Attention

 

*^13/6/2024

Eilam (zoom?):

Graph Neural Networks

 

Etienne:

GNN tutorial

 

Etienne:

homework 4:

Graph Neural Networks

 

20/6/2024

 

Nilotpal:

Diffusion

 

 

Dmitrii:

Diffusion tutorial

 

 

Nilotpal:

Bayesian NN
 

 

27/6/2024

Eilam:

Deep Reinforcement Learning

 

Dmitrii:

Deep Q-learning tutorial

 

 

Etienne:

Homework 5: policy gradient

 

4/7/2024 Project Proposals I          
11/7/2024 Project Proposals II.           
             
             

TBA
Take home
5 hours
From 9AM

Take Home Assignement          

TBA

11:00-16:00

Project Presentations (POSTERs festival)