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Thoughtful machine learning with python: a test-driven approach, matthew kirk

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Gain the confidence you need to apply machine learning in your daily work.
With this practical guide, author Matthew Kirk shows you how to integrate and
test machine learning algorithms in your code, without the academic subtext.

Featuring graphs and highlighted code examples throughout, the book features
tests with Python’s Numpy, Pandas, Scikit-Learn, and SciPy data science
libraries. If you’re a software engineer or business analyst interested in
data science, this book will help you:

Reference real-world examples to test each algorithm through engaging, hands-
on exercises

Apply test-driven development (TDD) to write and run tests before you start
coding

Explore techniques for improving your machine-learning models with data
extraction and feature development

Watch out for the risks of machine learning, such as underfitting or
overfitting data

Work with K-Nearest Neighbors, neural networks, clustering, and other
algorithms

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