Machine Learning with Spark and Python
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Machine Learning with Spark and Python
Machine Learning with Spark and Python: Essential Techniques for Predictive Analytics, Second Edition simplifies machine learning for practical uses by focusing on two key algorithms. This new second edition is enhanced with the addition of Spark, a machine learning framework from the Apache foundation. By implementing Spark, machine learning students can easily process much larger data sets and call the Spark algorithms using ordinary Python code.
Machine Learning with Spark and Python focuses on two algorithm familiesβlinear methods and ensemble methodsβthat effectively predict outcomes. This type of problem covers many use cases such as determining which ad to place on a web page, predicting prices in securities markets, or detecting credit card fraud. The concentration on these two families allows for comprehensive descriptions of the mechanisms at work within the algorithms.
The accompanying code examples serve to illustrate the workings of the machinery with specific, hackable code, making the concepts accessible and applicable for students and professionals alike.
Book Details
INFORMATION
ISBN: 9781119561934
Publisher: John Wiley & Sons Inc
Format: Paperback / softback
Date Published: 05 December 2019
Country: United States
Imprint: John Wiley & Sons Inc
Edition: 2nd edition
Audience: Professional and scholarly
DIMENSIONS
Spine width: 23.0mm
Width: 185.0mm
Height: 229.0mm
Weight: 612g
Pages: 368
About the Author
MICHAEL BOWLES teaches machine learning at UC Berkeley, University of New Haven and Hacker Dojo in Silicon Valley, consults on machine learning projects, and is involved in a number of startups in such areas as semi conductor inspection, drug design and optimization and trading in the financial markets. Following an assistant professorship at MIT, Michael went on to found and run two Silicon Valley startups, both of which went public. His courses are always popular and receive great feedback from participants.
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