ML Online Course 2021

Welcome to the Weizmann practical Deep Learning Online Course 2021

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

join slack channel

Your lecturers and TAs are
Sanmay Ganguly, Jonathan Shlomi, Nilotpal Kakati, 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 lectures are recorded and available

Date Lecture Slides
& Video
Tutorial 1 Slides
& Video
Tutorial 2 Slides
& Video
7/4/2021

Eilam:

Introduction

slides

Video of lecture and tutorials

Sanmay:

Intro to python

slides

notebook

 

 

Jonathan:

Pytorch

video

notebook

21/4/2021 Eilam:
Backpropagation

slides

video

Sanmay

Tutorial2:

continuation of basic python + pytorch

slides

codes

video

Jonathan:

homework 1

Galaxy 10 dataset

video for homework 1

invite link to homework

28/4/2021 Eilam:
Convolutional NN
slides

Sanmay:

CNNs

video (of eilam and sanmays lectures) optimisation,
regularisation

notebooks

video

slides

05/05/2021

Eilam:

CNN architectures and RNN

video

Sanmay:

RNNs

video (of eilam and sanmays lectures)

homework 2

transfer learning and denoising

video instructions

invite link to homework

19/05/2021

Jonathan:

Graph Neural Networks

video

slides

Sanmay:

GNN

notebooks

Video

Jonathan:

homework3

graph neural networks

video

invite link to homework

26/05/2021

Jonathan:

Attention is All You Need

video

slides

online video

Sanmay:

implementation

Video    
2/06/2021 Autoencoders

Video

Slides

video tutorial on autoencoders

notebook for autoencoder tutorial

Q&A about GNNs video

homework 4:

attention

homework 4 video

invite link to homework

9/06/2021

Eilam

GAN

slides

video

Sanmay:

Tutorial DCGAN

 

Tutorial DCGAN

Jonathan:

GAN

notebook for GAN tutorial

video for GAN tutorial

16/06/2021

 

Eilam:

Detection & Segmentation

Slides

Video

Sanmay: UNET

 

Video    
23/06/2021

Eilam:

Deep Reinforcement Learning

Slides

Video

Sanmay:

Bayesian NN

 

Video

Jonathan:

homework 5

policy optimisation

video instructions for homework 5

invite link

video from last year about DQN

30/06/2021 Projects 1          
7/07/2021 Projects 2          

11/07/2021
Take home
5 hours
From 9AM

Take Home Assignement          

15-17/
/08/2021
11:00-16:00

Project Presentations