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November 29, 2017 to December 1, 2017
Europe/Zurich timezone

What problem can you solve with machine learning and how?

Nov 29, 2017, 3:30 PM
Auditorium Shannon (LRI)

Auditorium Shannon


Batiment 660


Prof. Alexandre Gramfort (INRIA)


In this lecture I will cover the various families of problems that machine learning can solve. Using examples, primarily on images, I will present various linear and non-linear dimensionality reduction methods (PCA,NMF, T-SNE), I will motivate the use of certain clustering techniques (K-means, DBSCAN) and I will then explain which families of methods exist for building predictive models (linear methods, trees, nearest neighbors). I will insist on the computational aspects explaining the differences between batch and online learning which is necessary when data become too big to fit in RAM. This talk with be a live demo using the scikit-learn software.

Primary author

Prof. Alexandre Gramfort (INRIA)

Presentation materials

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