Introduction - If you have any usage issues, please Google them yourself
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.