Neural networks have made a surprise comeback in the last few years and have brought tremendous innovation in the world of artificial intelligence. The goal of this book is to provide C# programmers with practical guidance in solving complex computational challenges using neural networks and C# libraries such as CNTK, and TensorFlowSharp. This book will take you on a step-by-step practical journey, covering everything from the mathematical and theoretical aspects of neural networks, to building your own deep neural networks into your applications with the C# and .NET frameworks. This book begins by giving you a quick refresher of neural networks. You will learn how to build a neural network from scratch using packages such as Encog, Aforge, and Accord. You will learn about various concepts and techniques, such as deep networks, perceptrons, optimization algorithms, convolutional networks, and autoencoders. You will learn ways to add intelligent features to your .NET apps, such as facial and motion detection, object detection and labeling, language understanding, knowledge, and intelligent search. Throughout this book, you will be working on interesting demonstrations that will make it easier to implement complex neural networks in your enterprise applications.

The state-of-the-art methods used for relation classification are primarily based on statistical machine learning, and their performance strongly depends on the quality of the extracted features. The extracted features are often derived from the output of pre-existing natural language processing (NLP) systems, which leads to the propagation of the errors in the existing tools and hinders the performance of these systems.

使用python一步一步搭建起自己的神经网络，对理解神经网络原理大有裨益，强烈推荐！

recurrent neural network without a phd.pdf 出处：https://github.com/martin-gorner/tensorflow-rnn-shakespeare

Neural Network Methods for Natural Language Processing by Yoav Goldberg，上传的这个为英文版，方便大家看原版。中文版本为车万翔老师翻译的《基于深度学习的自然语言处理》

该压缩包包含了国外最新的Java神经网络教程，里面包含PDF教程与配套代码，供大家学习使用。

Neural Network Design Demonstrations(神经网络设计代码演示) 一个神经网络源程序教学任务包，里面有130个M文件，可直接调用，供大家参考。

For those entering the field of artificial neural networks, there has been an acute need for an authoritative textbook that explains the main ideas clearly and consistently using the basic tools of linear algebra, calculus, and simple probability theory. There have been many attempts to provide such a text, but until now, none has succeeded. Some authors have failed to separate the basic ideas and principles from the soft and fuzzy intuitions that led to some of the models as well as to most of the exaggerated claims. Others have been unwilling to use the basic mathematical tools that are essential for a rigorous understanding of the material. Yet others have tried to cover too many different kinds of neural network without going into enough depth on any one of them. The most successful attempt to date has been "Introduction to the Theory of Neural Computation" by Hertz, Krogh and Palmer. Unfortunately, this book started life as a graduate course in statistical physics and it shows. So despite its many admirable qualities it is not ideal as a general textbook.

MATLAB Neural Network Toolbox官方教程，包含入门教程，用户手册和参考手册

Single-Shot Refinement Neural Network for Object Detection论文翻译，纯手工