When comparing Reinforcement Learning: An Introduction vs Hacker's guide to Neural Networks (by Andrej Karpathy), the Slant community recommends Hacker's guide to Neural Networks (by Andrej Karpathy) for most people. In the question“What are the best resources to learn Machine Learning?” Hacker's guide to Neural Networks (by Andrej Karpathy) is ranked 5th while Reinforcement Learning: An Introduction is ranked 9th. The most important reason people chose Hacker's guide to Neural Networks (by Andrej Karpathy) is:
All theory introduced in this guide is nicely explained and backed up with concrete, straightforward examples that are easy to understand. The math-heavy parts are nicely illustrated with code, and the author walks you through each step of the process gently.
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Pros
Pro Has good balance between technical and non-technical information
Written to cover both the subject matter and theory.
Pro Covers 3 essential reinforcement learning approaches
The second part of the book covers Dynamic Programming, Monte Carlo Methods and Temporal Difference Learning learning methods. They're presented in an interesting way and explained through various examples.
Pro Approachable
Pro Offers lots of real world examples
Pro Free
Available online for free.
Pro Explanation of theories are easy to understand
All theory introduced in this guide is nicely explained and backed up with concrete, straightforward examples that are easy to understand. The math-heavy parts are nicely illustrated with code, and the author walks you through each step of the process gently.
Pro Great for programmers looking to get into machine learning
This guide assumes that the reader has some experience with programming and dives straight into the subject matter. It doesn't waste time on non-essentials, and it's geared toward readers looking to understand the building blocks of machine learning from the ground up.
Cons
Con Uses vague terms
Supplementary resources that have formalized the terms used in this book might be needed to fully understand everything.
Con Not suitable for beginners with no programming experience
If you're unfamiliar with programming, you might feel lost. This guide assumes the reader has some background in programming and dives straight into code.