本书是机器学习入门书，以Python语言介绍。主要内容包括：机器学习的基本概念及其应用；实践中最常用的机器学习算法以及这些算法的优缺点；在机器学习中待处理数据的呈现方式的重要性，以及应重点关注数据的哪些方面；模型评估和调参的高级方法，重点讲解交叉验证和网格搜索；管道的概念；如何将前面各章的方法应用到文本数据上，还介绍了一些文本特有的处理方法。(This book is an introduction to machine learning, introduced in Python language. The main contents include: the basic concepts and applications of machine learning; the most commonly used machine learning algorithms in practice and their advantages and disadvantages; the importance of presenting the data to be processed in machine learning, and what aspects of data should be focused on; advanced methods of model evaluation and parameter adjustment, focusing on cross validation and grid search; the concept of pipeline; how to The methods in the previous chapters are applied to text data, and some text specific processing methods are also introduced.)