Books & Courses

  • Starting with an introduction to RL, learn different RL environments and frameworks.
  • Learn to implement custom environments and use OpenAI baselines to run RL algorithms.
  • Explore RL techniques such as Dynamic Programming, Monte Carlo, and TD Learning.
  • Understand deep Q-learning, DARQN and policy-based method to tackle an RL problem.

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  • Hands-on approach to building smart applications.
  • On-Device machine learning with TensorFlow (Android and iOS).
  • TensorFlow for the web (TensorFlow.js).

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  • Practical examples and step-by-step instructions.
  • Build and optimize machine learning models.
  • Deep learning for computer vision.
  • Generative adversarial nets.
  • Deep reinforcement learning.

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SapientRazorfish_ Kepler Lab Team in Mint Lounge, Hindustan Times - Fri, Nov 17 2017.