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Summary

Machine learning Python — two book bundle!

Book 1: Artificial Intelligence with Python

What you will learn in this book:

  • Different artificial intelligence approaches and goals
  • How to define AI system
  • Basic AI techniques
  • Reinforcement learning
  • How to build a recommender system
  • Genetic and logic programming
  • And much, much more....

Book 2: Reinforcement Learning with Python

What you will learn by listening to this book:

  • Types of fundamental machine learning algorithms in comparison to reinforcement learning
  • Essentials of reinforcement learning process
  • Marko decision processes and basic parameters
  • How to integrate reinforcement learning algorithm using OpenAI Gym
  • How to integrate Monte Carlo methods for prediction
  • Monte Carlo tree search
  • Dynamic programming in Python for policy evaluation, policy iteration and value iteration
  • Temporal difference learning or TD
  • And much, much more....

Listen to this book bundle now and save money!

©2017 Anthony S. Williams (P)2017 Anthony S. Williams

What listeners say about Machine Learning Python: 2 Manuscripts - Artificial Intelligence Python and Reinforcement Learning with Python

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MACHINE LEARNING


I agree this may be currently the best textbook on machine learning.
And I would need to refer this book too for understanding or relative works.
Before buying this book, it could be helpful to think of the trait first.

18 people found this helpful

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would recommended

Would definitely recommend this book to colleagues of mine who are looking to learn more about AI and how it's used in business contexts. author did a superb job in bringing it all together in a single book that was much required by the community.

18 people found this helpful

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Enjoyed the lessons learned

I was pleasantly surprised to find there were many life lessons that could be used in all walks of life. It was easy to listen and understand the messages included regarding artificial intelligence and the effects on in the workplace. This book was an easy listen and the author is certainly well versed in the art of selling. Over the coming decades, AI will undoubtedly have a significant impact on the way we live, work, and make a living.

4 people found this helpful

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  • Barbara
  • 10-08-19

Best on Audible

I have tried some other AI courses on Audible but they all gloss over the math and it makes it seem like they have a surface level understanding of what is actually going on. In this course it is clear The Lazy Programmer knows the math behind the algorithms and does a good job at setting up the building blocks so that by the time you see Q-Learning at the bundle you will get Different artificial intelligence approaches and Types of fundamental machine learning algorithms in comparison to reinforcement learning goals and why it was important to first learn about multi armed bandit, MC, TD, etc. first. I'm also a huge fan of coding things by myself as I've done courses with Anthony S. Williams with "Reinforcement Learning with Python in 2018" in the past and that can be harder to actually understand since you might not see how the code ties in. Definitely would recommend.

33 people found this helpful

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  • Lillian Rooney
  • 10-08-19

Everything is clear

I have learned epsilon-greedy and UCB1. It prooved me I had very wrong idea about what RL is. My goal is to get to DL in RL and do some learning robots.

32 people found this helpful

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  • Bessie
  • 10-08-19

Understanding the whole idea of AI

Best introductory course on Reinforcement Learning you could ever find here. Be warned though that without an advanced knowledge of probability you won't get the most out of this course. The Genetic and logic programming also recommender system that forms the basis of Reinforcement Learning is the key to understanding the whole idea of AI

31 people found this helpful

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  • Jeffrey Hart
  • 10-08-19

Helped me be more natural

Yes, I know a lot about the math and theory but I am primarily an R user so the Python part will be new. That said, I really like how the instructor lays out the topic and the examples he uses. It will help me be more natural when I describe my project to others (including my professor).

28 people found this helpful

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  • Kathleen
  • 10-08-19

Many algorithms to implement

This is a really pratical course with many algorithms to implement. It's really helps me know more about the implementation details in reinforcement learning!

28 people found this helpful

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  • Scott Cooper
  • 10-08-19

Deep diving course

It is a very deep diving course, where one would need prerequisites in good python programming skill (I don't have). Further, the author offers many lectures from the basics up to toplevel skills, as I learned from the appendix, so it is highly recommended to follow the learning path.

28 people found this helpful

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  • Marilyn
  • 10-08-19

Right material to lay a foundation

Very thorough introduction and the right material to lay a foundation for further learning about RL

26 people found this helpful

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  • Sharon
  • 10-08-19

Strengthen NOW!

Even though I'd taken college courses on all the prerequisites of this course (probability, calculus etc), I realised that my foundations weren't strong enough. I'm glad that I got to know what to strengthen after taking this course!

24 people found this helpful

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  • Seth Neal
  • 10-08-19

Highly recommended

Great course! Very deep and thorough, and probably the most important of all - it forces you to apply what you learn and truly understand it. Highly recommended (!!!) for everyone serious about learning RL.

24 people found this helpful

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  • Kathy Bell
  • 10-08-19

Clear and concise.

Great course to start learning about these things. Clear and concise. What it lacks are references to source material for those who want to go a little bit deeper in understanding RL

23 people found this helpful