ML Course 2023 (Weissman Auditorum Tuesdays)

Welcome to the Weizmann practical Deep Learning Course 2023

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

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%).

All lecture slides and tutorial code will be posted below.

Date	Lecture	Slides & Video	Tutorial	Slides & Video	Tutorial 2	Slides & Video
18/4/2023	Eilam: Introduction	Lecture 1: Introduction	Etienne: Python essentials	python notebook	Etienne: NumPy and grad. desc.	numpy notebook grad. notebook
9/5/2023	Eilam: Backpropagation	Lecture 2 Back-propagation	Nilotpal pytorch	materials	Nilotpal: homework 1 Classification	GitHub assignment hw1 solution
16/5/2023	Eilam: Convolutional NN	Lecture 3	Nilotpal: CNNs	materials	Dmitrii: Optimisation, Regularisation	materials
23/5/2023	Eilam: CNN architectures and RNN	Lecture 4, CNN and RNN Lecture 4, CNN RNN Video	Eilam: GAN	GAN recording GAN PDF	Etienne: homework 2 transfer learning and denoising	Transfer learning notebooks hw2 solution
30/5/2023	Etienne: Autoencoders (VAE)	Lecture 5 VAE slides	Nilotpal: VAE tutorial	PDF materials	Nilotpal: DCGAN tutorial	PDF materials
6/6/2023	Eilam: Graph Neural Networks	GNN Lecture	Etienne: GNN tutorial	materials	Etienne: homework3 Graph Neural Networks	homework3 assignment hw3 solution
13/6/2023	Nilotpal: Attention is All You Need (Transformers)	Lecture 7: attention	Nilotpal: Attention tutorial	Material
27/6/2023	Eilam: Attenion on Attention Detection & Segmentation	Attention Segmentation	Nilotpal: UNET	Material	Etienne: Homework 4: Attention	homework4 overview recording homework4 assignment hw4 solution
4/7/2023	Nilotpal: Diffusion	Lecture slides	Dmitrii: Diffusion tutorial	Material	Nilotpal Bayesian NN	Bayesian NN
11/7/2023	Eilam: Deep Reinforcement Learning	Deep Reinforcement Learning	Dmitrii: Deep Q-learning tutorial	Recording Material	Etienne: Homework 5 Pong with policy gradient	homework5 overview recording homework5 assignment hw5 solution
18/7/2023	Project Proposals I
25/7/2023	Project Proposals II
TBA Take home 5 hours From 9AM	Take Home Assignement
TBA 11:00-16:00	Project Presentations (POSTERs festival)