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Sep 4-5, 2018: Training
Sep 5-7, 2018: Tutorials & Conference
San Francisco, CA

Reinforcement learning unchained: How to leverage machine teaching to build AI into complex, real-world systems

Mark Hammond (Microsoft)
11:55am-12:35pm Friday, September 7, 2018
Implementing AI
Location: Yosemite BC
Secondary topics:  Reinforcement Learning
Average rating: ****.
(4.00, 1 rating)

Who is this presentation for?

  • CIOs, data scientists, and developers

Prerequisite knowledge

  • Familiarity with programming

What you'll learn

  • Learn best practices for building and deploying deep reinforcement learning models for real-world enterprise systems


Building complex, real-world reinforcement learning systems requires leveraging techniques such as curriculum learning, hierarchical RL, and reward shaping. Without using these and other techniques to guide the learning, you can easily obtain irreproducible policies with odd behavior or fail to converge on a policy altogether. Machine teaching collects these techniques together, allowing you to formally codify how to teach effective policies leveraging subject-matter expertise and programming.

Mark Hammond explores many of these techniques and illustrates how they can be effectively combined into a comprehensive machine teaching program.

Photo of Mark Hammond

Mark Hammond


Mark Hammond is cofounder and CEO at Bonsai. Mark has a deep passion for understanding how the mind works and has been thinking about AI throughout his career. He has held positions at Microsoft and numerous startups and in academia, including turns at Numenta and in the Yale Neuroscience Department. He holds a degree in computation and neural systems from Caltech.