08 Dec '16, 11pm

My slides for distributed deep reinforcement learning on spark are up from @strataconf

Distributed deep rl on spark strata singapore 1. SKYMIND INTELLIGENCE LAYER (SKIL) REFERENCE ARCHITECTURE 2. Overview ● Why am I up here? ● Reinforcement Learning ● Use cases ● Demo! ● Deep Reinforcement Learning ● Rl4j ● Dl4j ● Spark/RL - why? 3. Why am I up here? Wrote this --> Book Giveaway! 4. Reinforcement Learning ● Learn a “policy” with repeated trial and error ● An agent explores a search space ● Learns from rewards and penalties each time it takes a step ● Think of win/lose scenarios ● Rewards/punishment set by an “environment” Credit: http://ai.berkeley.edu/reinforcement.ht ml 5. Use cases (not games!) ● Risk analysis (loans) ● Network Intrusion ● Learning patterns from simulations (MCMC) 6. Demo! Cartpole (Hello world of RL) 7. Deep Reinforcement Learning ● Teach a neural net from environment ● Policy determines gradient descent steps ● Most work has been based ...

Full article: http://www.slideshare.net/agibsonccc/distributed-deep-rl-...

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