Building machine learning-enabled products are hard for developers and data scientists; throw in a hardware component, and the complexity increases exponentially. Sunil Mallya walks you through how to build complex ML-enabled products using RL, explores hardware design challenges and trade-offs, and details real-life examples of how any developer can up level their RL skills through autonomous driving.
What you'll learn
- Learn how to build complex ML-enabled products using RL and about hardwire design challenges and trade-offs
- Hear real-life examples of how to level up your RL skills through autonomous driving
This session is from the 2019 O'Reilly Artificial Intelligence Conference in San Jose, CA. and is sponsored by Amazon Web Services.
- Title: Making reinforcement learning practical for real-world developers (sponsored by Amazon Web Services)
- Release date: February 2020
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 0636920370970
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