这是一个视频的字幕，使用方法见这里：https://blog.csdn.net/yj13811596648/article/details/89354314

Deep learning in neural networks: An overview In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarizes relevant work, much of it from the previous millennium. Shallow and Deep Learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation),unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.

Hopfield Neural Network——Hopfield神经网络的python代码，基于Language: Python 3.5.x，API: Google TensorFlow 1.0.x。实验案例有训练Hopfield网络对MNIST数字进行分类等。

Deep Neural Networks for YouTube Recommendations论文翻译

Make Your Own Neural Network---------mobi 、epub、azw3

MATLAB神经网络30个案例分析(高清）,适用于缺乏对于神经网络的matlab操作经验的童鞋。

Tree-Based Convolutional Neural Networks，Lili Mou • Zhi Jin。2018年新书，介绍基于树构造的卷积神经网络。

Neural Networks: Tricks of the Trade, Second Edition Editors: Grégoire Montavon, Geneviève B. Orr, Klaus-Robert Müller 有关神经网络、深度学习Tricks的入门经典书籍。

神经网路机器人机构及非线性系统控制，介绍了控制器的设计思路与稳定性证明，还是很详细的，推荐一下

A Guide to Convolutional Neural Networks for Computer Vision-Morgan & Claypool(2018).pdf