No detailed description available for "Angular and Machine Learning Pocket Primer".
About the Author: 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.
262 Pages
Computers, Human-Computer Interaction (HCI)
Series Name: Pocket Primer
Description
About the Book
As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic machine learning concepts and incorporate that knowledge into Angular applications. The book is intended to be a fast-paced introduction to some basic features of machine learning and an overview of several popular machine learning classifiers.
Book Synopsis
No detailed description available for "Angular and Machine Learning Pocket Primer".
About the Author
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).
Dimensions (Overall): 8.9 Inches (H) x 6.0 Inches (W) x .6 Inches (D)
Weight: .9 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 262
Genre: Computers
Sub-Genre: Human-Computer Interaction (HCI)
Series Title: Pocket Primer
Publisher: Mercury Learning and Information
Format: Paperback
Author: Oswald Campesato
Language: English
Street Date: April 25, 2020
TCIN: 1013398455
UPC: 9781683924708
Item Number (DPCI): 247-61-9046
Origin: Made in the USA or Imported
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Shipping details
Estimated ship dimensions: 0.6 inches length x 6 inches width x 8.9 inches height
Estimated ship weight: 0.9 pounds
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