The C Programming Language是C语言的经典书籍，程序员必备的学习、参考资料，这里把第二版的中文、英文原版和习题答案、高清电子版一起打包。

本书详细介绍了Ruby1.8和1.9版本各方面的内容。在对Ruby进行了简要的综述之后，本书详细介绍了以下内容：Ruby的句法和语法结构，数据结构和对象，表达式和操作符，语句和控制结构，方法、proc、lambda和闭包，反射和园变成，Ruby平台。

intel汇编语言程序设计最新版 使用MASM12汇编器,部分16位程序在64位系统上无法运行.从第5版开始进入x86汇编学习,是非常不错的入门书籍.

Java Language Specification（Java编程规范）中英文合集 这是我从网上分别下的中文版和英文版打包在一起的，希望能为你们节省很多搜索找寻时间，其中那个中文版真的很难找~~

This book attempts to simplify and present the concepts of deep learning in a very comprehensive manner, with suitable, full-fledged examples of neural network architectures, such as Recurrent Neural Networks (RNNs) and Sequence to Sequence (seq2seq), for Natural Language Processing (NLP) tasks. The book tries to bridge the gap between the theoretical and the applicable. It proceeds from the theoretical to the practical in a progressive manner, first by presenting the fundamentals, followed by the underlying mathematics, and, finally, the implementation of relevant examples. The first three chapters cover the basics of NLP, starting with the most frequently used Python libraries, word vector representation, and then advanced algorithms like neural networks for textual data. The last two chapters focus entirely on implementation, dealing with sophisticated architectures like RNN, Long Short-Term Memory (LSTM) Networks, Seq2seq, etc., using the widely used Python tools TensorFlow and Keras. We have tried our best to follow a progressive approach, combining all the knowledge gathered to move on to building a question- and-answer system. The book offers a good starting point for people who want to get started in deep learning, with a focus on NLP. All the code presented in the book is available on GitHub, in the form of IPython notebooks and scripts, which allows readers to try out these examples and extend them in interesting, personal ways.

Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning By 作者: Delip Rao – Brian McMahan ISBN-10 书号: 1491978236 ISBN-13 书号: 9781491978238 Edition 版本: 1 出版日期: 2019-02-11 pages 页数: (256 ) $89.99 Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems

北微传感器的驱动代码，可以读取pitch,roll,heading三个方向角度值，验证可用

该书为斯坦福大学撰写的教材，自然语言处理的教程，介绍了正则表达式、自然语言处理的诸多模型、算法，该书尚未完稿，内部有部分章节空缺，仍然不影响它成为一本优秀的自然语言处理教材，该文件为英文电子版！感兴趣的可以下载学习。

language(侦壳)/AspackDie(脱壳)/pw32dasmgold(反编译) 可用于破解.exe文件，破解教程https://blog.csdn.net/findsafety/article/details/49797695

源码支持PLC200/300/400与上位机进行通讯，采用S7协议