Welcome to the Weizmann practical Deep Learning Online Course 2021
All communication with the lecturers will be made via SLACK. join here:
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 |
Sanmay: Intro to python |
|
Jonathan: Pytorch |
||
| 21/4/2021 | Eilam: Backpropagation |
Sanmay Tutorial2: continuation of basic python + pytorch |
Jonathan: homework 1 Galaxy 10 dataset |
|||
| 28/4/2021 | Eilam: Convolutional NN |
slides |
Sanmay: CNNs |
video (of eilam and sanmays lectures) | optimisation, regularisation |
|
| 05/05/2021 |
Eilam: CNN architectures and RNN |
video |
Sanmay: RNNs |
video (of eilam and sanmays lectures) |
homework 2 transfer learning and denoising |
|
| 19/05/2021 |
Jonathan: Graph Neural Networks |
Sanmay: GNN |
Jonathan: homework3 graph neural networks |
|||
| 26/05/2021 |
Jonathan: Attention is All You Need |
Sanmay: implementation |
Video | |||
| 2/06/2021 | Autoencoders | Q&A about GNNs video |
homework 4: attention |
|||
| 9/06/2021 |
Eilam GAN |
Sanmay: Tutorial DCGAN
|
Tutorial DCGAN |
Jonathan: GAN |
||
| 16/06/2021 |
Eilam: Detection & Segmentation |
Sanmay: UNET
|
Video | |||
| 23/06/2021 |
Eilam: Deep Reinforcement Learning |
Sanmay: Bayesian NN
|
Video |
Jonathan: homework 5 policy optimisation |
||
| 30/06/2021 | Projects 1 | |||||
| 7/07/2021 | Projects 2 | |||||
|
11/07/2021 |
Take Home Assignement | |||||
|
15-17/ |
Project Presentations |