Machine Learning in Action by Peter Harrington

Machine Learning in Action by Peter Harrington

Summary

Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll 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.

About the Book

A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interestingor useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many.

Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you'll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data visualization in code you can reuse. You'll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification.

Readers need no prior experience with machine learning or statistical processing. Familiarity with Python is helpful.

Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

What's Inside

• A no-nonsense introduction
• Examples showing common ML tasks
• Everyday data analysis
• Implementing classic algorithms like Apriori and Adaboos

Table of Contents

PART 1 CLASIFICATION
1. Machine learning basics
2. Classifying with k-Nearest Neighbors
3. Splitting datasets one feature at a time: decision trees
4. Classifying with probability theory: naive Bayes
5. Logistic regression
6. Support vector machines
7. Improving classification with the AdaBoost meta algorithm
PART 2 FORECASTING NUMERIC VALUES WITH REGRESION
8. Predicting numeric values: regression
9. Tree-based regression
PART 3 UNSUPERVISED LEARNING
10. Grouping unlabeled items using k-means clustering
11. Association analysis with the Apriori algorithm
12. Efficiently finding frequent itemsets with FP-growth
PART 4 ADITIONAL TOLS
13. Using principal component analysis to simplify data
14. Simplifying data with the singular value decomposition
15. Big data and MapReduce

Peter Harrington, a native of Manchester, England, is currently the curator of the Anne S. K. Brown Military Collection at the John Hay Library of Brown University, Rhode Island, USA. He is an authority on artists and war and has written extensively on the subject, including British Artists and War: The Face of Battle in Paintings and Prints (1993), as well as organising a number of exhibitions on war art. This is his third book in the Osprey Campaign series, his others being Campaign 12: Culloden 1746 and Campaign 35: Plassey 1757.

SKU	Unavailable
ISBN 13	9781617290183
ISBN 10	1617290181
Title	Machine Learning in Action
Author	Peter Harrington
Condition	Unavailable
Binding Type	Paperback
Publisher	Manning Publications
Year published	2012-04-24
Number of pages	384
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
Note	Unavailable