文件名称：Thoughtful Machine Learning with Python A Test-Driven Approach
文件大小：3.36MB
文件格式：AZW3
更新时间：2021-10-13 06:05:06
python machine learning
The Plan for the Book This book will cover a lot of ground with machine learning, but by the end you should have a better grasp of how to write machine learning code as well as how to deploy to a production environment and operate at scale. Machine learning is a fascinating field that can achieve much, but without discipline, checklists, and guidelines, many machine learning projects are doomed to fail. Throughout the book we will tie back to the original principles in this chapter by talking about SOLID principles, testing our code (using various means), and refactoring as a way to continually learn from and improve the performance of our code. Every chapter will explain the Python packages we will use and describe a general testing plan. While machine learning code isn’t testable in a one-to-one case, it ends up being something for which we can write tests to help our knowledge of the problem.