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book: Python 3 for Machine Learning
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Python 3 for Machine Learning

  • Oswald Campesato
Language: English
Published/Copyright: 2020
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About this book

This book is designed to provide the reader with basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fundamental concepts of machine learning. The sixth chapter is devoted to machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on NLP and RL. Keras-based code samples are included to supplement the theoretical discussion. The book also contains separate appendices for regular expressions, Keras, and TensorFlow 2.

Features:

  • Provides the reader with basic Python 3 programming concepts related to machine learning
  • Includes separate appendices for regular expressions, Keras, and TensorFlow 2

Author / Editor information

Campesato Oswald :

Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the NLP Using R Pocket Primer (all Mercury Learning and Information).

Reviews

Programmers who want to get up to speed in Python 3 will appreciate O. Campesato's Python 3 for Machine Learning, a survey of basic Python 3 programming concepts, applications, expressions, and machine learning relationships. This introduction is packed with supporting mathematical, programming, and statistical information and summarizes each chapter's machine learning components, making it an excellent self study guide."

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Publishing information
Pages and Images/Illustrations in book
eBook published on:
February 21, 2020
eBook ISBN:
9781683924937
Paperback published on:
March 16, 2020
Paperback ISBN:
9781683924951
Pages and Images/Illustrations in book
Main content:
364
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