Thoughtful Machine Learning A Test-Driven Approach
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Sprache:Englisch
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eBook Format:PDF
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inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Ja
Text-to-Speech
Nein
Erscheinungsdatum
26.09.2014
Verlag
O'Reilly MediaSeitenzahl
236 (Printausgabe)
Dateigröße
5640 KB
Sprache
Englisch
EAN
9781449374105
Learn how to apply test-driven development (TDD) to machine-learning algorithmsand 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 cant 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 youre familiar with Ruby 2.1, youre ready to start.Apply TDD to write and run tests before you start codingLearn the best uses and tradeoffs of eight machine learning algorithmsUse real-world examples to test each algorithm through engaging, hands-on exercisesUnderstand the similarities between TDD and the scientific method for validating solutionsBe aware of the risks of machine learning, such as underfitting and overfitting dataExplore techniques for improving your machine-learning models or data extraction
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