LASA - Machine Learning Courses

Aude Billard, École polytechnique fédérale de Lausanne (EPFL)

1 April 2020, 55 videos, 26706 views, Open Channel, Podcast RSS feed

This channel contains lectures in support of the following three EPFL Master-level courses I teach at EPFL:

  • Applied Machine Learning
  • Machine Learning Programming
  • Advanced Machine Learning

These videos are to be watched prior to coming to class. Please, check the class's website to know which video you should watch first. 

These videos are made available to the public, so that researchers world-wide can benefit from this material. This is meant especially for those who have to study from home, or those from countries with limited access to education.  

Beware that these videos are meant to be used in flipped classes. The video lectures are complemented with live interactive exercise sessions and practice sessions, given to EPFL students.

Enjoy and do not hesitate to send feedback: aude.billard@epfl.ch

Viewable by everyone.

22:23

Lecture 1 | Part 1, Introduction to Machine Learning

6 September 2020, 1443 views

7:53

Lecture 1 | Part 2 , Pitfalls and Caveats in Machine Learning

6 September 2020, 870 views

11:21

Lecture 2 | Part 1, Principal Component Analysis - Principle

9 September 2020, 937 views

7:53

Lecture 2 | Part 2, PCA - Intuition

9 September 2020, 871 views

15:35

Lecture 2 | Part 3 , PCA - Derivation

13 September 2020, 1037 views

11:08

Lecture 3 | Part 1, Clustering Principle

2 October 2020, 808 views

14:28

Lecture 3 | Part 2-1, K-means

2 October 2020, 826 views

17:03

Lecture 3 | Part 2 -2 , Soft K-means & DBSCAN

4 October 2020, 776 views

20:38

Lecture 3 | Part 3, Evaluation for Clustering

4 October 2020, 830 views

26:01

Lecture 4 | Part 1, Recap of Probabilities and Densities (optional)

13 October 2020, 790 views

12:10

Lecture 4 | Part 2, Fitting data with one Gauss function

11 October 2020, 797 views

17:49

Lecture 4 | Part 3, Fitting and clustering data with Mixture of Gauss Functions

11 October 2020, 931 views

19:14

Lecture 4 | Part 4, Probabilistic Interpr. of K-Means & GMM

17 October 2020, 784 views

4:30

Lecture 5 | Part 1, Classification - Introduction

23 October 2020, 648 views

20:30

Lecture 5 | Part 2, Classification with GMM

23 October 2020, 744 views

11:24

Lecture 5 | Part 3, KNN Classifier

23 October 2020, 701 views

31:55

Lecture 5 | Part 4, Metrics for classification

25 October 2020, 684 views

7:12

Lecture 6 Part 1, SVM - Principle

3 November 2020, 724 views

17:00

Lecture 6 Part 2, Linear SVM derivation

3 November 2020, 766 views

31:55

Lecture 6 | Part 3, Quantifying performance

25 October 2020, 40 views

3:07

Lecture 6 Part 3, SVM for Non-separable datasets

3 November 2020, 632 views

12:34

Lecture 6 Part 4, Nonlinear SVM

3 November 2020, 636 views

3:45

Lecture 6 Part 5 , SVM Hyperparameters

3 November 2020, 582 views

5:44

Lecture 6 | Part 6, Multiclass SVM

4 November 2020, 569 views

11:27

Lecture 6 | Part 7, Pros & Cons of SVM

4 November 2020, 604 views

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