Upgrade_SiteFactory.Standard_3.0.0.0-3.1.0.0

说明：  多用户检测的PPT 很基本 但很重的一些原理 (POWERPOINT OF MUD)

C音频教程，基础教程，经典(C Audio Guide, Basic Course, Classic)

说明：  《深度学习》由全球知名的三位专家Ian Goodfellow、Yoshua Bengio 和Aaron Courville撰写，是深度学习领域奠基性的经典教材。全书的内容包括3个部分：第1部分介绍基本的数学工具和机器学习的概念，它们是深度学习的预备知识；第2部分系统深入地讲解现今已成熟的深度学习方法和技术；第3部分讨论某些具有前瞻性的方向和想法，它们被公认为是深度学习未来的研究重点。(Deep learning, written by three famous experts in the world, is a classic textbook in the field of deep learning. The book consists of three parts: the first part introduces the basic mathematical tools and the concept of machine learning, which are the preparatory knowledge of deep learning; the second part systematically explains the mature deep learning methods and technologies; the third part discusses some forward-looking directions and ideas, which are recognized as the future research focus of deep learning.)

MATLAB GUI设计学习手册 第二版，适合初学者学习matlab gui(the book about matlab/gui)

说明：  有助于学习理解模拟电子技术,里面内容主要为一些上课用到的PPT课件(It will teach you how to learn Basis of Analogue Electronic Technique well.)

Latex必备书籍之一Tobias Oetiker著作，共六章，包括最基础的入门操作、索引、公式和比较难的图形等，完全够写一篇论文(One of the Necessary Books of Latex)

算法第四版书籍，经典书籍。学习算法的人员可以将此作为入门书籍。(Algorithm fourth edition, classic books.Learning algorithm of the researchers could see this as the introductory books.)

彩票中的数学lottery problem.pdf(lottery math lottery problem.pdf)

FPGA modelsim 仿真详细说明介绍(Modelsim operation manul, detail expain how to use modelsim)

说明：  本书由Keras之父、现任Google A工智能研究员的弗朗索瓦?肖莱（Frangois Chollet）执笔，详尽介 绍了用Python和Keras进行深度学习的探索实践，涉及计算机视觉、自然语言处理、生成式模型等应用。 书中包含30多个代码示例，步骤讲解详细透彻。由于本书立足于人工智能的可达性和大众化，读者无须 具备机器学习相关背景知识即可展开阅读。在学习完本书后，读者将具备搭建自己的深度学习环境、建立 图像识别模型、生成图像和文字等能力(This book is written by Frangois Chollet, the father of keras and the current researcher of Google a intelligence. It introduces in detail the exploration and practice of deep learning with Python and keras, involving computer vision, natural language processing, generative model and other applications. The book contains more than 30 code examples, and the steps are detailed and thorough. Because this book is based on the accessibility and popularization of artificial intelligence, readers can read it without having the background knowledge of machine learning. After learning this book, readers will have the ability to build their own deep learning environment, establish image recognition model, and generate images and characters)