July 2025
Intermediate to advanced
320 pages
3h 10m
Chinese
Overview
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通过详细的注释、表格和示例，这本实用参考手册将帮助您掌握结构化机器学习的基础知识。作者马特·哈里森（Matt Harrison）提供了一本宝贵的指南，您可以在训练过程中作为额外支持使用，并在深入下一个机器学习项目时作为便捷资源参考。
本书适合程序员、数据科学家和人工智能工程师，内容涵盖机器学习流程概述，并通过结构化数据分类示例逐步讲解。您还将学习聚类分析、连续值预测（回归）以及维度缩减等方法。
这本便携参考手册包含以下章节：
- 分类，使用泰坦尼克号数据集
- 数据清洗与缺失值处理
- 探索性数据分析
- 使用示例数据进行常见预处理步骤
- 选择对模型有用的特征
- 模型选择
- 指标与分类评估
- 使用k最近邻、决策树、提升等方法的回归示例
- 回归评估指标
- 聚类
- 维度缩减
- Scikit-learn 管道
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