EE-608 Deep Learning For Natural Language Processing

Alireza Mohammadshahi, École polytechnique fédérale de Lausanne (EPFL)

13 October 2021, 22 videos, 125 views, Open Channel

The Deep Learning for NLP course provides an overview of neural network based methods applied to text. The focus is on models particularly suited to the properties of human language, such as categorical, unbounded, and structured representations, and very large input and output vocabularies. 

Viewable by everyone.

55:14

part1, Lecture 07

5 November 2021, 11 views

39:05

part1, Lecture 10

25 November 2021, 5 views

1:01:29

Part 1, Lecture 04

14 October 2021, 24 views

1:00:33

part 1, Lecture 05

26 October 2021, 9 views

54:42

part 1, Lecture 06

28 October 2021, 8 views

40:58

part 1, Lecture 09

25 November 2021, 1 view

47:26

part 1, Lecture 12 - The Future

22 December 2021, 1 view

42:39

Part 2, Lecture 03

14 October 2021, 11 views

26:49

Part 2, Lecture 04

14 October 2021, 12 views

29:35

part 2, Lecture 05

26 October 2021, 2 views

37:01

part 2, Lecture 06

29 October 2021, No views

24:45

part 2, Lecture 07

5 November 2021, 2 views

28:44

part 2, Lecture 09

25 November 2021, 1 view

29:09

part 2, Lecture 10

25 November 2021, 1 view

31:26

part 2, Lecture 12 - The future

22 December 2021, No views

54:33

Exercise Session 1, Intro to Pytorch, Word Embeddings

14 October 2021, 11 views

51:50

Exercise Session 2, Intro to Pytorch 2, NLP Tools

14 October 2021, 7 views

1:12:27

Exercise session 3 - Training an RNN classifier with mean/max pooling and project proposals

15 October 2021, 9 views

49:14

Exercise session 4 - Seq2Seq models with and without attention

22 October 2021, 3 views

1:44:58

Exercise session on pitfalls in empirical NLP research

25 November 2021, 4 views

1:14:39

Lecture 11 - Model Analysis

2 December 2021, 1 view

58:36

Lecture 13 - Variational Autoencoders

23 December 2021, 2 views