现货 Thoughtful Machine Learning: A Test-Driven Approach 英文原版 机器学习实践 测试驱动的开发方法 Matthew Kirk
美国原版，未使用过，近全新，现货一本。
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北京昌平
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作者Matthew Kirk
出版社O'Reilly Media, Inc, USA
ISBN9781449374068
出版时间2014
装帧平装
页数234页
货号X701
上书时间2019-04-18
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- 美国原版，未使用过，近全新，图片实拍，现货一本。
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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
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