AutoML, Peer mentoring and Coursera course discussion

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Tura.io

2828 SW Corbett Ave #200 · Portland, OR

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Lets get together to discuss all aspects of deep learning.

In particular, this week I'm interested in learning more about AutoML (learning to learn). If you get a chance and are so inclined check out Using Machine Learning to Explore Neural Network Architecture (https://research.googleblog.com/2017/05/using-machine-learning-to-explore.html) and Google Vizier: A Service for Black-Box Optimization.

Our own Sylvain Payot will lead a short talk titled: AlphaGo: How DeepMind put an end to 2,500 years of human mastery

The game of Go has long been viewed as the most challenging of classic games for artificial intelligence combining an enormous search space and a challenging evaluation of board positions and moves.

In this talk, we walk you through the strategy adopted by Google DeepMind to develop the program AlphaGo, building on state of the art reinforcement learning and deep learning techniques to defeat some of the world’s greatest Go champions in 2016.

And finally, bring any questions you may have on the Fast.AI or Andrew Ng's coursera course.

All levels of experience are welcome. We rarely have presentations, though we may someone leads a discussion. Bring your questions, projects and ideas, basic or advanced, and we'll try to help.

Don't forget the #deep-learning channel in the PDX Startups slack which you can join at https://pdx-startups-slack.herokuapp.com (https://pdx-startups-slack.herokuapp.com/)

Resources:

https://www.coursera.org/learn/neural-networks-deep-learning/

http://course.fast.ai

http://www.deeplearningbook.org (http://www.deeplearningbook.org/)