Thoughtful Machine Learning with Python: A Test-Driven Approach

Matthew Kirk

Thoughtful Machine Learning with Python: A Test-Driven Approach

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商品描述

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

商品描述(中文翻譯)

在你的日常工作中，獲得應用機器學習所需的信心。在這本實用指南中，作者Matthew Kirk向你展示如何在代碼中集成和測試機器學習算法，而不需要學術背景。

本書中包含了圖表和突出的代碼示例，並使用Python的Numpy、Pandas、Scikit-Learn和SciPy數據科學庫進行測試。如果你是一名軟件工程師或業務分析師，對數據科學感興趣，這本書將幫助你：

- 通過引人入勝的實踐練習，參考真實世界的示例來測試每個算法
- 在編寫代碼之前，應用測試驅動開發（TDD）來編寫和運行測試
- 探索通過數據提取和特徵開發來改進機器學習模型的技術
- 注意機器學習的風險，例如欠擬合或過擬合數據
- 使用K-最近鄰算法、神經網絡、聚類和其他算法進行工作

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