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Applied Reinforcement Learning with Python - by  Taweh Beysolow II (Paperback) - 1 of 1

Applied Reinforcement Learning with Python - by Taweh Beysolow II (Paperback)

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About this item

Highlights

  • Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python.
  • About the Author: Taweh Beysolow II is a data scientist and author currently based in the United States.
  • 168 Pages
  • Computers + Internet, Intelligence (AI) & Semantics

Description



Book Synopsis



Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym.

Applied Reinforcement Learning with Python introduces you to the theory behind reinforcement learning (RL) algorithms and the code that will be used to implement them. You will take a guided tour through features of OpenAI Gym, from utilizing standard libraries to creating your own environments, then discover how to frame reinforcement learning problems so you can research, develop, and deploy RL-based solutions.


What You'll Learn

  • Implement reinforcement learning with Python
  • Work with AI frameworks such as OpenAI Gym, Tensorflow, and Keras
  • Deploy and train reinforcement learning-based solutions via cloud resources
  • Apply practical applications of reinforcement learning

Who This Book Is For

Data scientists, machine learning engineers and software engineers familiar with machine learning and deep learning concepts.



From the Back Cover



Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym.

Applied Reinforcement Learning with Python introduces you to the theory behind reinforcement learning (RL) algorithms and the code that will be used to implement them. You will take a guided tour through features of OpenAI Gym, from utilizing standard libraries to creating your own environments, then discover how to frame reinforcement learning problems so you can research, develop, and deploy RL-based solutions.


What You'll Learn:

  • Implement reinforcement learning with Python
  • Work with AI frameworks such as OpenAI Gym, Tensorflow, and Keras
  • Deploy and train reinforcement learning-based solutions via cloud resources
  • Applypractical applications of reinforcement learning



About the Author



Taweh Beysolow II is a data scientist and author currently based in the United States. He has a Bachelor of Science degree in economics from St. Johns University and a Master of Science in Applied Statistics from Fordham University. After successfully exiting the startup he co-founded, he now is a Director at Industry Capital, a San Francisco based Private Equity firm, where he helps lead the Cryptocurrency and Blockchain platforms.
Dimensions (Overall): 9.21 Inches (H) x 6.14 Inches (W) x .4 Inches (D)
Weight: .59 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 168
Genre: Computers + Internet
Sub-Genre: Intelligence (AI) & Semantics
Publisher: Apress
Format: Paperback
Author: Taweh Beysolow II
Language: English
Street Date: August 24, 2019
TCIN: 85084695
UPC: 9781484251263
Item Number (DPCI): 247-48-5467
Origin: Made in the USA or Imported
If the item details aren’t accurate or complete, we want to know about it.

Shipping details

Estimated ship dimensions: 0.4 inches length x 6.14 inches width x 9.21 inches height
Estimated ship weight: 0.59 pounds
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Q: What programming language is primarily used in this book?

submitted by AI Shopping Assistant - 8 days ago
  • A: The book primarily uses Python to demonstrate the implementation of reinforcement learning algorithms.

    submitted byAI Shopping Assistant - 8 days ago
    Ai generated

Q: Which frameworks are utilized in this book's examples?

submitted by AI Shopping Assistant - 8 days ago
  • A: Examples in the book utilize AI frameworks such as OpenAI Gym, Tensorflow, and Keras for practical applications.

    submitted byAI Shopping Assistant - 8 days ago
    Ai generated

Q: Who is the target audience for this book?

submitted by AI Shopping Assistant - 8 days ago
  • A: The book is aimed at data scientists, machine learning engineers, and software engineers familiar with deep learning.

    submitted byAI Shopping Assistant - 8 days ago
    Ai generated

Q: What key topics are covered in this book?

submitted by AI Shopping Assistant - 8 days ago
  • A: The book covers policy gradients, Q learning, and uses frameworks like Tensorflow, Keras, and OpenAI Gym.

    submitted byAI Shopping Assistant - 8 days ago
    Ai generated

Q: How many pages does this book contain?

submitted by AI Shopping Assistant - 8 days ago
  • A: The book contains a total of 168 pages, providing comprehensive insights into reinforcement learning.

    submitted byAI Shopping Assistant - 8 days ago
    Ai generated

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