Thoughtful Machine Learning with Python: A Test-Driven Approach
暫譯: 深思熟慮的機器學習與 Python：測試驅動的方法

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)

獲得在日常工作中應用機器學習所需的信心。這本實用指南的作者 Matthew Kirk 向您展示如何在代碼中整合和測試機器學習算法，而不需要學術背景。

本書中包含圖表和突出顯示的代碼範例，並使用 Python 的 Numpy、Pandas、Scikit-Learn 和 SciPy 數據科學庫進行測試。如果您是對數據科學感興趣的軟體工程師或商業分析師，這本書將幫助您：

- 參考現實世界的範例，通過引人入勝的實作練習來測試每個算法
- 應用測試驅動開發（TDD），在開始編碼之前編寫和運行測試
- 探索改進機器學習模型的技術，包括數據提取和特徵開發
- 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、神經網絡、聚類及其他算法進行工作

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