Cours

EE-613: Machine Learning for Engineers

Résumé

The objective of this course is to give an overview of machine learning techniques used for real-world applications, and to teach how to implement and use them in practice. Laboratories will be done in python using jupyter notebooks.

Séances de cours

Enseignant·e·s (4)

Jean-Marc Odobez

Enseignement et PhD Doctorant·es actuel·les Vivek Samir Gupte, Yesmine Abdennadher, Samy Tafasca, Shalutha Navindu Rajapakshe Rajapakshe Mudiyanselage, Gökhan Özbulak, Karl El Hajal, Hasindri Sankalpana Watawana, Mingchi Hou, Pierre François Marie Vuillecard, João Pedro Gandarela de Souza, Anirban Mukherjee, Elija Maria Vida, Nawal Haidar, Mojtaba Nafez A dirigé les thèses EPFL de Jagannadan Varadarajan, Alexandre Heili, Samira Sheikhi, Kenneth Alberto Funes Mora, Do Hoang Nam Le, Christian Jaques, Yu Yu,

Sylvain Calinon

Expertise robot learning, human-robot collaboration, optimal control, model-based optimization I am a Senior Research Scientist at the Idiap Research Institute and a Lecturer at EPFL, with research interests covering robot learning, optimal control, geometrical approaches, and human-robot collaboration. My work focuses on human-centered robotics applications in which the robots can acquire new skills from only few demonstrations and interactions. It requires the development of models that can exploit the st

Olivier Canévet

Enseignement et PhD Cours Machine Learning for Engineers EE-613

Michael Villamizar

Enseignement et PhD Cours Machine Learning for Engineers EE-613

Source officielle

Page Moodle

http://go.epfl.ch/EE-613

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Résumé

Séances de cours

Enseignant·e·s (4)

Jean-Marc Odobez

Sylvain Calinon

Olivier Canévet

Enseignement et PhD Cours Machine Learning for Engineers EE-613

Michael Villamizar

Enseignement et PhD Cours Machine Learning for Engineers EE-613

Source officielle

Page Moodle

http://go.epfl.ch/EE-613

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