Machine Learning in Action

Peter Harrington

ISBN: 9789350044131

380 pages

INR 899

Description

“Machine Learning in Action” is a unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. In it, you will use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification. As you work through the numerous examples, you will explore key topics like classification, numeric prediction, and clustering. Along the way, you will be introduced to important established algorithms, such as Apriori, through which you identify association patterns in large datasets and Adaboost, a meta-algorithm that can increase the efficiency of many machine learning tasks. This book is written for hobbyists and developers. A background in Java is helpful-no prior experience with Android is assumed.

 

Part 1- Classification

· Machine learning basics

· Classifying with k-Nearest Neighbors

· Splitting datasets one feature at a time: decision trees

· Classifying with probability theory: naïve Bayes

· Logistic regression

· Support vector machines 101

· Improving classification with the AdaBoost meta-algorithm

 

Part 2- Forecasting Numeric Values With Regression

· Predicting numeric values: regression 153

· Tree-based regression

 

Part 3- Unsupervised Learning

· Grouping unlabeled items using k-means clustering

· Association analysis with the Apriori algorithm

· Efficiently finding frequent itemsets with FP-growth

 

Part 4- Additional Tools

· Using principal component analysis to simplify data

· Simplifying data with the singular value decomposition

· Big data and MapReduce

 

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