This book is written for two kinds of readers. The first type of reader is one who plans to study Deep Learning in a systematic approach for further research and development. This reader should read all the content from the beginning to end. The example code will be especially helpful for further understanding the concepts. A good deal of effort has been made to construct adequate examples and implement them. The code examples are constructed to be easy to read and understand. They are written in MATLAB for better legibility. There is no better programming language than MATLAB at being able to handle the matrices of Deep Learning in a simple and intuitive manner. The example code uses only basic functions and grammar, so that even those who are not familiar with MATLAB can easily understand the concepts. For those who are familiar with programming, the example code may be easier to understand than the text of this book. The other kind of reader is one who wants more in-depth information about Deep Learning than what can be obtained from magazines or newspapers, yet doesn’t want to study formally. These readers can skip the example code and briefly go over the explanations of the concepts. Such readers may especially want to skip the learning rules of the neural network.

Pytorch神经网络编程学习记录

Learning WebRTC随书配套代码。 WebRTC是一个支持网络浏览器进行实时语音对话或视频对话的软件架构。本书使用形象的案例介绍，逐步深入地阐述了 WebRTC 的幕后工作原理。通过阅读本书，读者可以快速、有效地掌握创建一个 WebRTC 应用所必需的知识，包括获取用户设备信息、创建 WebRTC 应用的客户端和服务器、连接用户并发送数据、文件共享、数据信息安全和性能优化。

Deep Learning (Ian Goodfellow, Yoshua Bengio and Aaron Courville)深度学习中英文版本资源-附件资源

本书可作为精益生产相关从业人员的研究、参考资料，也可以作为高等院校工业工程及相关专业本科生和研究生的教材。

OpenJDK Cookbook

经典的模式识别与机器学习教材的课后习题Pattern Recognition and Machine Learning习题答案

在这些教程中，我们将演示和可视化遗传算法，进化策略，NEAT等算法。 下文提到的所有方法都有其中文视频和文本教程。 请访问 。 捐款 如果这样做对您有帮助，请考虑捐赠以支持我以获得更好的教程！ 任何贡献都将不胜感激！

路径规划问题，有三种环境配置可实现，以下是代码来源，基于此做的实验 https://blog.csdn.net/jacken3/article/details/119803094

Reinforcement Learning - An Introduction 2nd 2017