We have created a Paris Machine Learning group on LinkedIn. You might want to join us there.
We also organize Meetups on the subject of Machine Learning and its applications. If you are in the area at some point in time and willing to give a talk, please contact me. We currently aim for those meetings to be held the second Wednesday of the month.
Our next Paris Machine Learning Meetup (#4) will take place at DojoEvents on Wednesday October 16th and will feature some Bayesian talks:
- Bayesian Programming and Learning for Multi-Player Video Games, Gabriel Synnaeve
- Hierarchical Modeling, Partial Pooling, and the Virtual Database Query, Andrew Gelman
First, Gabriel Synnaeve will talk to us about how he used Bayesian formalism to develop bots for Starcraft. Then, Andrew Gelman (you may have heard of his blog Statistical Modeling, Causal Inference, and Social Science) will talk to us about hierarchical models and how they were applied to think differently about US voting patterns/behaviors. His book on the subject Red State, Blue State, Rich State, Poor State:Why Americans Vote the Way They Do has received considerable coverage as his use of hierarchical modeling and voting data has provided a refreshing insight on traditional held view in U.S. politics. Andrew's other textbooks can be found here [1]. Both talks are slated to be in French with (most probably) slides in English.
We will also probably have a small introductory talk at the beginning of the meetup. If you are interested in attending any of these talks, or simply want to interact with the rest of the community before and after the talks, by all means inscrivez vous.
Si vous vous inscrivez, et que pour une raison ou une autre, vous ne pouvez pas venir, Franck, Frederic and moi apprecierions que vous changiez votre RSVP avant le meeting. Nous ne voulons pas rentrer dans des considerations de files d'attentes et nous vous serions extremement reconnaissant si vous aviez le reflexe de vous decommander, meme au dernier moment. De notre cote, nous faisons tout notre possible pour qu'il reste une trace de ce meeting de facon a faire en sorte que meme si vous n'etiez pas la, vous avez une possibilite d'entrevoir ce qui a ete dit. Aidez -nous a rendre ces meetings possibles en rendant l'organisation la plus simple possible. Nous comptons sur vous..
[1] http://www.stat.columbia.edu/~gelman/books/
Join the CompressiveSensing subreddit or the Google+ Community and post there !
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.
No comments:
Post a Comment