资源简介
Author:
Matthew Kirk
ISBN-10:
1491924136
Year: 2017
Pages: 216
Language: English
File size: 8.6 MB
File format:PDF
Category: Data Mining
Book Description:
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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