Processing ......
FreeComputerBooks.com
Free Computer, Mathematics, Technical Books and Lecture Notes, etc.
 
Python Machine Learning Projects
Want to know the Homepage of a particular airport? Click here to find out.
  • Title Python Machine Learning Projects
  • Author(s) Brian Boucheron, Lisa Tagliaferri
  • Publisher: DigitalOcean (2019)
  • License(s): CC BY-NC-SA 4.0
  • Hardcover/Paperback N/A
  • eBook PDF (135 Pages), ePub, and Mobi (Kindle)
  • Language: English
  • ISBN-10: N/A
  • ISBN-13: 978-0999773024
  • Share This:  

Book Description

This book tries to equip the developers of today and tomorrow with tools they can use to better understand, evaluate, and shape machine learning.

It will set you up with a Python programming environment if you don’t have one already, then provide you with a conceptual understanding of machine learning in the chapter "An Introduction to Machine Learning." What follows next are three Python machine learning projects. They will help you create a machine learning classifier, build a neural network to recognize handwritten digits, and give you a background in deep reinforcement learning through building a bot for Atari.

If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource.

Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.

About the Authors
  • Brian Boucheron is Senior Technical Writer at DigitalOcean. Writes about Kubernetes, Linux, and programming.
  • Lisa Tagliaferri is Senior Manager of Developer Education at DigitalOcean. She is a Digital Humanities researcher at Villa I Tatti, The Harvard University Center for Italian Renaissance Studies.
Reviews, Ratings, and Recommendations: Related Book Categories: Read and Download Links: Similar Books:
Book Categories
Other Categories
Resources and Links