机器学习实战 第2版 : 基于Scikit-Learn、Keras和TensorFlow
机器学习实战（原书第2版） :基于Scikit-Learn、Keras和TensorFlow， 这本机器学习畅销书基于tensorflow 2和scikit learn的新版本进行了全面更新。通过具体的示例，很少有可用于生产环境的理论和python框架，它可以帮助您直观地理解和掌握从头构建智能系统所需的概念和工具。
这本书分为两部分。第一部分介绍了机器学习的基础知识，包括以下主题：什么是机器学习，它试图解决什么问题，以及系统的主要类别和基本概念；第二部分介绍了神经网络和深度学习，包括以下主题：什么是神经网络及其用途，使用tensorflow和keras构建和训练神经网络的技术，以及如何使用强化学习构建可以通过试错学习好策略的代理。第一部分主要基于scikit学习，而第二部分使用tensorflow和keras。
通过这本书，你将学习一系列可以快速使用的技巧。每章中的练习可以帮助你应用所学知识。您只需要一些编程经验。所有代码都可以在GitHub上找到。
This machine learning bestseller has been comprehensively updated based on the new versions of tensorflow 2 and scikit learn. Through specific examples, very few theories and python frameworks that can be used in production environments, it helps you intuitively understand and master the concepts and tools needed to build intelligent systems from scratch.
The book is divided into two parts. The first part introduces the basics of machine learning, covering the following topics: what is machine learning, what problems it tries to solve, and the main categories and basic concepts of the system; The second part introduces neural networks and deep learning, covering the following topics: what are neural networks and what they are used for, the technology of using tensorflow and keras to build and train neural networks, and how to use reinforcement learning to build agents that can learn good strategies through trial and error. The first part is mainly based on scikit learn, while the second part uses tensorflow and keras.
Through this book, you will learn a series of techniques that can be used quickly. The exercises in each chapter can help you apply what you have learned. You only need some programming experience. All the code is available on GitHub.