Course taught in the Data and Knowledge 2nd year Master Program of Université Paris Saclay
2018-2019
The objective of this course is to be a first course on machine learning and data mining algorithms from a practical and a theoretical point of view. This is an introductory course that will set the basis for the more advanced courses on the second period. Topics covered include:
– classification
– regression
– clustering
Instructors: Rodrigo Fernandes de Mello (Télécom ParisTech) and Albert Bifet (Télécom ParisTech)
Evaluation:
- 1/3 Lab Assignments
- 2/3 Final Test
Lecture Slides
- 0 – Introduction to Machine Learning and Data Science Slides
- 1 – Introduction. Source code.
- 2 – The Perceptron. Source code.
- 3 – Multilayer Perceptron. Source code.
- 4 – scikit-learn Lab Slides (due 10th October 2018) Submission
- 5 – Bayesian Learning. Source code.
- 6 – R Lab Slides (due 24th October 2018) Submission
- 7 – Decision Trees. Source code.
- 8 – Ensembles. Source code.
- 9 – Kaggle Lab Slides (due 9th November 2018) Submission