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Page 1: Teaching ML with scikit-learn at Telecom ParisTech

Teaching machine learning withscikit-learn:

The Telecom ParisTech Experiment

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Alexandre GramfortTelecom ParisTech - CNRS LTCI

[email protected]

GitHub : @agramfort Twitter : @agramfort

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The Telecom ParisTech Experim

ent

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>>> import sklearn

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History

>>> import sklearn

From

To

$ RR version 2.15.1 (2012-06-22) -- …Copyright (C) 2012 The R Foundation for Statistical Computing>

or

< M A T L A B (R) > Copyright 1984-2012 The MathWorks, Inc. R2012b (8.0.0.783) 64-bit (glnxa64) August 22, 2012>>

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HistoryFrom

To

16 students in ML class in 2012

> 60 students in ML class in 2016

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Alexandre Gramfort Teaching with scikit-learn

Formations

6

• Ingénieur Télécom, filière Sciences des Données

• M2 Data Science (Télécom & Polytechnique)

• M2 Data & Knowledge (Télécom, Paris Sud, Polytechnique)

• M2 DataScale (UVSQ, ENSIIE, Télécom, Télécom SudParis)

• Mastère Spécialisé « Big Data : gestion et analyse des données massives »

• Certificat d’études spécialisées «Data Scientist»

• MOOC Fondamentaux du Big Data

http://www.telecom-paristech.fr/cartobigdata

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Alexandre Gramfort Teaching with scikit-learn

Filière Science des Données (SD)

7

1er semestre 2eme semestre

Période 1 Période 2 Période 3 Période 4

SD201 Exploration des grands volumes de données

SD203 Développement Web

SD210 Bases de l'apprentissage statistique

SD211 Optimisation pour l'apprentissage statistique

SD202 Bases de données

SD204 Statistique : modèles linéaires

SD205 Statistique avancée : estimation non paramétrique et théorie de l’apprentissage

SD207 Apprentissage statistique par la pratique

Team effort:• > 10 faculties (MdC, Professors)• with help from PhD students / Postdocs in ML

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SD210 - SD207: ≈50% hands on

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Challenges

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Can’t stop working !I need to win the

challenge

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Doing datascience with challenges

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Doing datascience with challenges

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Doing datascience with challenges

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Alexandre [email protected]:

GitHub : @agramfort Twitter : @agramfort

Questions?

1 position to work on Scikit-Learn and Scipy stack available !