迁移学习简明手册-王晋东

https://github.com/jindongwang/transferlearning-tutorial

变分自编码器VAE技术解析

https://blog.csdn.net/roguesir/article/details/81263442

https://blog.csdn.net/kingfoulin/article/details/92073101

https://yuanxiaosc.github.io/2018/08/26/%E5%8F%98%E5%88%86%E8%87%AA%E7%BC%96%E7%A0%81%E5%99%A8/

元学习：从小样本到快速强化学习(ICML19 tutorial) 

https://blog.csdn.net/naipp/article/details/95621454

ADMM算法简介

https://www.zhihu.com/question/36566112

https://blog.csdn.net/shanglianlm/article/details/45919679

https://blog.csdn.net/oBanTianYun/article/details/72590188

https://joegaotao.github.io/2014/02/11/admm-stat-compute/

https://www.cnblogs.com/kailugaji/p/10433774.html

https://www.zhihu.com/question/36566112/answer/118715721

http://shijun.wang/2016/01/19/admm-for-distributed-statistical-learning/

深度学习中常用梯度优化方法

https://blog.csdn.net/u014595019/article/details/52989301

https://zhuanlan.zhihu.com/p/36327151

https://www.cnblogs.com/zingp/p/11352012.html

https://github.com/exacity/simplified-deeplearning/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E4%B8%AD%E7%9A%84%E4%BC%98%E5%8C%96/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E4%B8%AD%E7%9A%84%E4%BC%98%E5%8C%96.md

http://pelhans.com/2019/04/09/deepdive_tensorflow-note1/

遗传算法原理 

https://blog.csdn.net/u010451580/article/details/51178225

https://zhuanlan.zhihu.com/p/28328304

https://blog.csdn.net/piaoxuezhong/article/details/78634630

https://www.cnblogs.com/maybe2030/p/4665837.html

算法基础

https://github.com/ustcwpz/USTC-CS-Courses-Resource/tree/master/%E5%A4%A7%E4%B8%89%E4%B8%8A/%E7%AE%97%E6%B3%95%E5%9F%BA%E7%A1%80

tflite转文本

https://blog.csdn.net/SilentOB/article/details/86479442

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/schema/schema.fbs

https://blog.csdn.net/limtyty/article/details/96430640

https://www.stacknoob.com/s/GLtp4vqnYigjeCpYC5gMZV

http://techblog.youdao.com/?p=1335

https://github.com/qiulongquan/android_face_detection

https://www.cnblogs.com/YouXiangLiThon/p/10131071.html

RL系列分析之DDPG算法

https://blog.csdn.net/kenneth_yu/article/details/78478356

https://zhuanlan.zhihu.com/p/25239682

https://zhuanlan.zhihu.com/p/36506567

https://antkillerfarm.github.io/drl/2019/06/19/DRL_4.html

https://www.cnblogs.com/pinard/p/10345762.html

人脸识别和神经风格转换

https://zhuanlan.zhihu.com/p/52709899

https://blog.csdn.net/sinat_27421407/article/details/80487441

https://yq.aliyun.com/articles/570174

https://alberthg.github.io/2018/04/12/deeplearning-ai-c4w4/

https://baozoulin.gitbook.io/dl-ai-special-notebook/course4/di-si-zhou-te-shu-ying-yong-ren-lian-shi-bie-he-shen-jing-feng-ge-zhuan-huan-specialapplicationsface

自然语言处理与词嵌入

https://blog.csdn.net/qq_39521554/article/details/86696202

https://blog.csdn.net/Hansry/article/details/80399054

https://alberthg.github.io/2019/01/12/deeplearning-ai-c5w2/http://wangxin123.com/2018/03/02/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86%E4%B8%8E%E8%AF%8D%E5%B5%8C%E5%85%A5/

https://zhuanlan.zhihu.com/p/26287104

循环序列模型

https://blog.csdn.net/sinat_33761963/article/details/80195636

https://blog.csdn.net/weixin_41043240/article/details/79415134

https://moluchase.github.io/2018/02/03/dl11/

https://zhuanlan.zhihu.com/p/53035761

https://zhuanlan.zhihu.com/p/42014018

https://fengxc.me/%E5%90%B4%E6%81%A9%E8%BE%BE%E5%BA%8F%E5%88%97%E6%A8%A1%E5%9E%8B%EF%BC%9A%E5%BE%AA%E7%8E%AF%E5%BA%8F%E5%88%97%E6%A8%A1%E5%9E%8B.html

卷积神经网络_实例探究

https://blog.csdn.net/weixin_42234769/article/details/89852772?depth_1-utm_source=distribute.pc_relevant.none-task&utm_source=distribute.pc_relevant.none-task

https://www.jianshu.com/p/fa101fb95a09

https://blog.csdn.net/qq_27806947/article/details/88088327

https://github.com/AlbertHG/Coursera-Deep-Learning-deeplearning.ai/tree/master/04-Convolutional%20Neural%20Networks/week2

https://blog.csdn.net/qq_44806305/article/details/105119907https://blog.csdn.net/weixin_42234769/article/details/89852772?depth_1-utm_source=distribute.pc_relevant.none-task&utm_source=distribute.pc_relevant.none-task

pytorch深度学习框架入门与实践

https://zhuanlan.zhihu.com/p/31712507

https://github.com/chenyuntc/pytorch-book

https://cloud.tencent.com/developer/article/1094996

卷积神经网络

https://blog.csdn.net/rogerchen1983/article/details/90271393

https://blog.csdn.net/qq_41185868/article/details/79995732

AdaNet神经网络

https://blog.csdn.net/qq_41185868/article/details/84063488

基于单目图像来估计图像深度

https://blog.csdn.net/roslei/article/details/78813014

https://blog.csdn.net/jishijian7408/article/details/94881662

SENet

https://zhuanlan.zhihu.com/p/32702350

https://github.com/hujie-frank/SENet

Google人脸识别FaceNet原理分析

https://zhuanlan.zhihu.com/p/24837264

https://blog.csdn.net/stdcoutzyx/article/details/46687471

https://www.cnblogs.com/zyly/p/9703614.html

https://www.cnblogs.com/carle-09/p/10455484.html

https://bbs.huaweicloud.com/blogs/133648

随机森林原理解读

https://blog.csdn.net/wfei101/article/details/74840091

https://blog.csdn.net/y0367/article/details/51501780

https://zhuanlan.zhihu.com/p/54286825

https://cloud.tencent.com/developer/article/1387715

https://www.jiqizhixin.com/articles/2017-07-31-3

SVM原理解读

http://www.lipingjx.com/ai_artical/ailearning/5QW000.html

https://blog.csdn.net/v_JULY_v/article/details/7624837

https://zhuanlan.zhihu.com/p/31886934

https://cloud.tencent.com/developer/article/1594537

https://flashgene.com/archives/86454.html

XGBoost算法解读

https://zhuanlan.zhihu.com/p/90520307

https://zhuanlan.zhihu.com/p/36794802

https://snaildove.github.io/2018/10/02/get-started-XGBoost/

https://www.csuldw.com/2019/07/20/2019-07-20-xgboost-theory/

https://blog.csdn.net/w928485096/article/details/90107568

https://blog.csdn.net/matrix_zzl/article/details/78635221

https://ask.hellobi.com/article/6836

Mask RCNN原理分析

https://blog.csdn.net/ghw15221836342/article/details/80084861

https://blog.csdn.net/linolzhang/article/details/71774168

https://blog.csdn.net/jiongnima/article/details/79094159

https://blog.csdn.net/hnshahao/article/details/81231211

https://zhuanlan.zhihu.com/p/42745788

https://zhuanlan.zhihu.com/p/37998710

https://www.cnblogs.com/wangyong/p/9305347.html

https://www.cnblogs.com/wangyong/p/10614898.html

机器学习算法-决策树、SVM、随机森林

https://blog.csdn.net/accumulate_zhang/article/details/77542193

https://blog.csdn.net/yuanfu1998/article/details/81307665

https://www.bilibili.com/read/cv506824/

Faster RCNN原理分析与解读

https://zhuanlan.zhihu.com/p/82185598

https://blog.csdn.net/WYR_try/article/details/90582693

https://blog.csdn.net/qinchao315/article/details/80950583

https://zpehome.github.io/2019/08/23/faster-rcnn%E6%BA%90%E4%BB%A3%E7%A0%81%E5%88%86%E6%9E%90(%E4%B8%80)/

https://hongbb.top/2019/01/18/faster-rcnn/

MobileNet核心技术之卷积分解

https://zhuanlan.zhihu.com/p/80177088

https://blog.csdn.net/qq_38807688/article/details/84590717

https://blog.csdn.net/c20081052/article/details/80703896

https://github.com/Ewenwan/MVision/tree/master/CNN/MobileNet

https://www.yanxishe.com/columnDetail/17712

数据进行归一化为什么这么重要

https://blog.csdn.net/zenghaitao0128/article/details/78361038

https://blog.csdn.net/suv1234/article/details/72629459

https://www.jianshu.com/p/95a8f035c86c

https://zhuanlan.zhihu.com/p/40563426

SSD目标检测原理分析 

https://blog.csdn.net/wfei101/article/details/78157723

https://blog.csdn.net/qq_16540387/article/details/81563807

https://cloud.tencent.com/developer/article/1052779

http://lanbing510.info/2017/08/28/YOLO-SSD.html

https://www.cnblogs.com/fariver/p/7347197.html

深度神经网络的量化与压缩

https://zhuanlan.zhihu.com/p/50938836

https://zhuanlan.zhihu.com/p/36051603

https://blog.csdn.net/zbgjhy88/article/details/80945528

https://www.jiqizhixin.com/articles/2018-06-01-11

https://blog.csdn.net/qq_21997625/article/details/88203343

https://antkillerfarm.github.io/dl%20acceleration/2019/07/22/DL_acceleration_4.html

正交信号：复数，但不复杂

http://www.chinadmd.com/file/u6oticasiip3oixie3truvzu_1.html

caffe入门教程1——Caffe代码层次：Blob、Layer、Net、Solver

https://blog.csdn.net/Tian_fourpieces/article/details/79397453

anaconda  

Anaconda是一个免费开源的Python和R语言的发行版本，用于计算科学（数据科学、机器学习、大数据处理和预测分析），Anaconda致力于简化包管理和部署。

https://repo.continuum.io/archive/Anaconda3-5.1.0-Windows-x86_64.exe

caffe的solver中不同学习策略(lr_policy)分析及应用 

https://blog.csdn.net/cuijyer/article/details/78195178

https://blog.csdn.net/chen1234520nnn/article/details/98870661

http://yanjoy.win/page/11/

Caffe模型参数量（weights）计算

https://blog.csdn.net/FreeApe/article/details/71522174

https://blog.csdn.net/a8039974/article/details/77249703

Docker 的基本使用

https://yeyouluo.github.io/2017/11/11/docker-cmd/

https://www.runoob.com/docker/docker-image-usage.html

Caffe官方教程中译本

https://github.com/541435721/caffe/blob/master/Caffe%E5%AE%98%E6%96%B9%E6%95%99%E7%A8%8B%E4%B8%AD%E8%AF%91%E6%9C%AC_CaffeCN%E7%A4%BE%E5%8C%BA%E7%BF%BB%E8%AF%91(caffecn.cn).pdf

其他：

https://blog.csdn.net/FIELDOFFIER/article/details/44264715

https://blog.csdn.net/Leonis_v/article/details/50519811

https://blog.csdn.net/u010402786/article/details/50519922

https://blog.csdn.net/Xin_101/article/details/88767078

http://ibillxia.github.io/blog/2013/04/06/Convolutional-Neural-Networks/

支持向量机(SVM)

https://raw.githubusercontent.com/liuzheng712/Intro2SVM/master/Intro2SVM.pdf

https://blog.csdn.net/v_JULY_v/article/details/7624837

https://www.cnblogs.com/sddai/p/5723880.html

案例:

https://zhuanlan.zhihu.com/p/38597894

逻辑回归

逻辑回归 logistic regression 算法原理及优化

逻辑回归简化

Logistic回归

逐步了解Logistic回归

关于Logistic回归/a>

使用单层感知器神经网络（SLPNN）进行Logistic回归

机器学习课程：第2部分-SVM，感知器和Logistic回归

机器学习---三种线性算法的比较（线性回归，感知机，逻辑回归）（Machine Learning Linear Regression Perceptron Logistic Regression Co...

感知机、线性回归、逻辑回归的简单对比

Logistic回归：牛顿迭代法

分类-1-逻辑回归（Logistic regression）、感知学习算法（perceptron learning algorithm）、牛顿迭代法

CRF++源码解读

crf-tagging

go-coding-in-go-way

如何写出优雅的 Go 语言代码

基本分类模型入门指南：逻辑回归和SVM

深度学习和神经网络简介-用于新手的深度学习（1）

McCulloch-Pitts神经元—人类第一个生物神经元的数学模型

神经网络学习 之 M-P模型

MP神经元和感知器

支持向量机-机器学习算法简介

支持向量机解释

McCulloch-Pitts神经元与Perceptron模型

两种算法之间的混战-神经网络与支持向量机

感知器，SVM和内核方法

支持向量机（SVM）

深度学习何时比SVM或RandomForests®更好？

人工神经网络比支持向量机有什么优势

支持向量机与Logistic回归

比较SVM和逻辑回归

CRF 及CRF++ 安装与解释

【windows下CRF++的安装与使用】

这里简要介绍一下CRF++使用的命令格式、参数调整、模板制作的基本过程。

https://zhuanlan.zhihu.com/p/39695509

条件随机场（CRF）及CRF++安装使用

条件随机场 (CRF 入门)——工具包介绍

AI知识图谱：机器学习、深度学习、数据分析、数据挖掘「附脑图」

机器学习知识图谱

【机器学习】：机器学习算法图谱

机器学习算法地图（高清图）

【机器学习】机器学习知识图谱：传统学习、神经网络、深度学习、强化学习、对抗学习等

AI之math：人工智能概念之机器学习/深度学习中的数学基础知识图谱(最全)

https://cloud.tencent.com/developer/article/1387715