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TensorFlow and deep reinforcement learning, without a PhD (Google I/O '18)

On the forefront of deep learning research is a technique called reinforcement learning, which bridges the gap between academic deep learning problems and ways in which learning occurs in nature in weakly supervised environments. This technique is heavily used when researching areas like learning how to walk, chase prey, navigate complex environments, and even play Go. This session will teach a neural network to play the video game Pong from just the pixels on the screen. No rules, no strategy coaching, and no PhD required. Rate this session by signing-in on the I/O website here → https://goo.gl/mh5Wi8 Watch more TensorFlow sessions from I/O '18 here → https://goo.gl/GaAnBR See all the sessions from Google I/O '18 here → https://goo.gl/q1Tr8x Subscribe to the TensorFlow channel → https://goo.gl/ht3WGe #io18 event: Google I/O 2018; re_ty: Publish; product: TensorFlow - General; fullname: Martin Gorner, Yu-Han Liu; event: Google I/O 2018;