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Thoughtful Machine Learning: A Test-Driven Approach

✍ Scribed by Matthew Kirk


Publisher
O’Reilly Media
Year
2014
Tongue
English
Leaves
235
Category
Library

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✦ Synopsis


Learn how to apply test-driven development (TDD) to machine-learning algorithmsβ€”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.


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