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Machine Learning with Spark and Python: Essential Techniques for Predictive Analytics
Authors: Michael Bowles
ISBN-10 书号: 1119561930
ISBN-13 书号: 9781119561934
Edition 版本: 2
Publisher Finelybook 出版日期: 2019-11-05
pages 页数: 368 pages
Book Description
Machine Learning with Spark and Python Essential Techniques for Predictive Analytics,Second Edition simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves with the addition of Spark―a ML framework from the Apache foundation. By implementing Spark,machine learning students can easily process much large data sets and call the spark algorithms using ordinary Python code.
Machine Learning with Spark and Python focuses on two algorithm families (linear methods and ensemble methods) that effectively predict outcomes. This type of problem covers many use cases such as what ad to place on a web page,predicting prices in securities markets,or detecting credit card fraud. The focus on two families gives enough room for full descriptions of the mechanisms at work in the algorithms. Then the code examples serve to illustrate the workings of the machinery with specific hackable code.
Introduction
CHAPTER 1: The Two Essential Algorithms for Making Predictions
CHAPTER 2: Understand the Problem by Understanding the Data
CHAPTER 3: Predictive Model Building: Balancing Performance,Complexity,and Big Data
CHAPTER 4: Penalized Linear Regression
CHAPTER 5: Building Predictive Models Using Penalized Linear Methods
CHAPTER 6: Ensemble Methods
CHAPTER 7: Building Ensemble Models with Python
Index
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