Thoughtful Machine Learning: A Test-Driven Approach - Softcover

Kirk, Matthew

Softcover

ISBN 10: 1449374069 ISBN 13: 9781449374068

Publisher: O′Reilly, 2014

Synopsis

Learn how to apply test-driven development (TDD) to machine-learning algorithms—and catch mistakes that could sink your analysis. In this practical guide, author Matthew Kirk takes you through the principles of TDD and machine learning, and shows you how to apply TDD to several machine-learning algorithms, including Naive Bayesian classifiers and Neural Networks.

Machine-learning algorithms often have tests baked in, but they can’t account for human errors in coding. Rather than blindly rely on machine-learning results as many researchers have, you can mitigate the risk of errors with TDD and write clean, stable machine-learning code. If you’re familiar with Ruby 2.1, you’re ready to start.

• Apply TDD to write and run tests before you start coding
• Learn the best uses and tradeoffs of eight machine learning algorithms
• Use real-world examples to test each algorithm through engaging, hands-on exercises
• Understand the similarities between TDD and the scientific method for validating solutions
• Be aware of the risks of machine learning, such as underfitting and overfitting data
• Explore techniques for improving your machine-learning models or data extraction

About this title

About the Author

Matthew Kirk holds a B.S. in Economics and a B.S. in Applied and Computational Mathematical Sciences with a concentration in Quantitative Economics from the University of Washington. He started Modulus 7, a data science and Ruby development consulting firm, in early 2012. Matthew has spoken around the world about using machine learning and data science with Ruby.

Edition details

• Publisher: O′Reilly
• Publication date: 2014
• Language: English
• ISBN 10: 1449374069
• ISBN 13: 9781449374068
• Binding: Paperback
• Edition number: 1
• Number of pages: 236