LASA - Machine Learning Courses

Aude Billard, École polytechnique fédérale de Lausanne (EPFL)

1 April 2020, 56 videos, 28614 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.

17:19

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

22 September, 28 views

28:18

Lecture 12 | Part 1 (Advanced Machine Learning), Linear and kernel CCA

12 June 2021, 109 views

11:44

Lecture 8 | Part 3, Ridge Regression

14 May 2021, 19 views

38:21

Lecture 19 | Part 1 (Lecture 10 - Advanced Machine Learning), Discrete Reinforcement Learning

3 May 2021, 153 views

26:28

Lecture 18 | Part 1 (Lec 9 - Advanced Machine Learning), Gaussian Process Regression

26 April 2021, 173 views

21:05

Lecture 17 | Part 2 - (Lec 7) Advanced Machine Learning, SVR Extensions: Nu-SVR and RVR

14 April 2021, 125 views

26:53

Lecture 14 | (Lec 4) Advanced Machine Learning, Spectral Clustering and Laplacian Eigenmaps

23 March 2021, 163 views

21:49

Lecture 13 | (Lec 3) Advanced Machine Learning, Kernel K-means

14 March 2021, 181 views

26:01

Lecture 11 | (Lec 2) Advanced Machine Learning, Kernel PCA

1 March 2021, 213 views

11:13

Lecture 9 | Part 2, Comparison-GMR-SV

2 December 2020, 546 views

24:15

Lecture 9 | Part 1, Gaussian Mixture Regression

2 December 2020, 926 views

26:05

Lecture 8 | Part 3, Support Vector Regression (SVR)

23 November 2020, 749 views

14:05

Lecture 8 | Part 2 , Linear & Weighted Regression

22 November 2020, 618 views

6:09

Lecture 8 | Part 1, Regression Introduction

21 November 2020, 609 views

28:13

Lecture 7 | Part 2, Neural Networks: Multi-layers

10 November 2020, 467 views

32:41

Lecture 7 | Part 3, Deep neural networks and more

10 November 2020, 340 views

29:10

Lecture 7 | Part 1, Neural Networks: Perceptron

10 November 2020, 520 views

11:27

Lecture 6 | Part 7, Pros & Cons of SVM

4 November 2020, 606 views

5:44

Lecture 6 | Part 6, Multiclass SVM

4 November 2020, 570 views

5:27

Lecture 6 | Part 7, SVM Summary

3 November 2020, 17 views

3:45

Lecture 6 Part 5 , SVM Hyperparameters

3 November 2020, 583 views

12:34

Lecture 6 Part 4, Nonlinear SVM

3 November 2020, 638 views

3:07

Lecture 6 Part 3, SVM for Non-separable datasets

3 November 2020, 634 views

17:00

Lecture 6 Part 2, Linear SVM derivation

3 November 2020, 772 views

7:12

Lecture 6 Part 1, SVM - Principle

3 November 2020, 725 views

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