edwardzcl / Deep-learning-beginner

A simple document for deep learning beginner

深度学习/机器学习入门路线(精简版)

一、两大神经网络类型数学理论；

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二、用matlab实现基本神经网络；

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三、Tensorflow实现基本神经网络

这个的话，网上资料很多，我只提供典型的几个。

1. 港科大tensorflow：
2. tensorflow中文社区：
3. 这篇博客很细致：

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下面推荐一个书单：

电子版可百度，纸质版可以去图书馆借。

Tensorflow实战

Tensorflow实战 谷歌深度学习框架

Python机器学习 (美) 塞巴斯蒂安·拉施卡著 = Python machine learning Sebastian Raschka 高明, 徐莹, 陶虎成译 eng

TensorFlow机器学习项目实战 = Building machine learning projects with TensorFlow (阿根廷) Rodolfo Bonnin著 姚鹏鹏译 eng

MATLAB计算机视觉与深度学习实战 刘衍琦 ... [等] 编著

深度学习原理与TensorFlow实践 喻俨, 莫瑜主编 王琛, 胡振邦, 高杰著

深度学习轻松学 核心算法与视觉实践 冯超著

自己动手写神经网络 葛一鸣著

深入浅出深度学习 原理剖析与Python实践 黄安埠著

神经网络导论 王晓梅编著

关于量化：

多查引用与被引，自己发现领域Top团队。

[1] Learning to Train a Binary Neural Network
[2] Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations
[3] Bi-Real Net: Binarizing Deep Network towards Real-Network Performance
[4] All Binarized Convolutional Neural Network and Its implementation on an FPGA
[5] Towards Accurate Binary Convolutional Neural Network
[6] Accelerating Binarized Convolutional Neural Networks with Software-Programmable FPGAs
[7] BiDet: An Efficient Binarized Object Detector
[8] Joint Neural Architecture Search and Quantization
[9] BMXNet: An Open-Source Binary Neural Network Implementation Based on MXNet
[10] Quantized Convolutional Neural Networks for Mobile Devices
[11] Toward Extremely Low Bit and Lossless Accuracy in DNNs with Progressive ADMM
[12] Quantization Networks