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Description: 深度学习入门教程&&优秀文章&&Deep Learning Tutorial. Contribute to mppcasc/DeepLearning development by creating an account on GitHub.

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https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#deeplearning-tutorial
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#一-入门资料
完备的 AI 学习路线，最详细的中英文资源整理https://zhuanlan.zhihu.com/p/64052743
AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLhttps://github.com/apachecn/AiLearning
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#数学基础
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master/notes/Images/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%92%8C%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E7%9A%84%E6%95%B0%E5%AD%A6%E5%9F%BA%E7%A1%80.png
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#机器学习基础
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#快速入门
机器学习算法地图http://www.tensorinfinity.com/paper_18.html
机器学习 吴恩达 Coursera个人笔记https://github.com/Mikoto10032/DeepLearning/blob/master/books/%5BML-Coursera%5D%5B2014%5D%5BAndrew%20Ng%5D/%5B2014%5D%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E4%B8%AA%E4%BA%BA%E7%AC%94%E8%AE%B0%E5%AE%8C%E6%95%B4%E7%89%88v5.1.pdf
视频（含官方笔记）https://www.coursera.org/learn/machine-learning
百页机器学习http://themlbook.com/wiki/doku.php
机器学习 吴恩达 cs229个人笔记https://github.com/Mikoto10032/DeepLearning/blob/master/books/%5BML-CS229%5D%5B2011%5D%5BAndrew%20NG%5D/%5B2011%5D%E6%96%AF%E5%9D%A6%E7%A6%8F%E5%A4%A7%E5%AD%A6%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E8%AF%BE%E7%A8%8B%E4%B8%AA%E4%BA%BA%E7%AC%94.pdf
官网（笔记）http://cs229.stanford.edu/
视频（中文字幕）http://open.163.com/special/opencourse/machinelearning.html
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#深入理解
《模式识别与机器学习》 Christopher Bishophttps://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%A8%A1%E5%BC%8F%E8%AF%86%E5%88%AB%E4%B8%8E%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0PRML_Chinese_vision.pdf
《机器学习》 周志华https://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%91%A8%E5%BF%97%E5%8D%8E.pdf
《机器学习实战》 PelerHarringtonhttps://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%AE%9E%E6%88%98%20%E4%B8%AD%E6%96%87%E5%8F%8C%E9%A1%B5%E7%89%88.pdf
机器学习与深度学习书单https://mp.weixin.qq.com/s?__biz=MzAxMjcyNjE5MQ==&mid=2650488718&idx=1&sn=815a79d27d500f0fb8db1fe1fc6cfe48&chksm=83a2e54eb4d56c58a0989654f920d64ad2784ce52e4b2bc6883974257cf475c9983f05fb88c1&scene=0&xtrack=1&ascene=14&devicetype=android-28&version=27000339&nettype=WIFI&abtest_cookie=AwABAAoACwATAAQAI5ceAFaZHgDQmR4A3JkeAAAA&lang=zh_CN&pass_ticket=oEB1108Pes6HkdxEITmBjTb2Glju5%2BEGqHZKz50fMg0rgK4l9Fodlbe%2FDm96iX57&wx_header=1
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#深度学习基础
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#快速入门-1
深度学习思维导图https://github.com/dformoso/deeplearning-mindmap
深度学习算法地图http://www.tensorinfinity.com/paper_158.html
《斯坦福大学深度学习基础教程》 Andrew Ng（吴恩达）https://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%96%AF%E5%9D%A6%E7%A6%8F%E5%A4%A7%E5%AD%A6-%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E5%9F%BA%E7%A1%80%E6%95%99%E7%A8%8B.pdf
深度学习 吴恩达 个人笔记http://www.ai-start.com/dl2017/
视频http://mooc.study.163.com/smartSpec/detail/1001319001.htm
MIT深度学习基础-2019视频课程https://deeplearning.mit.edu/
台湾大学（NTU）李宏毅教授课程http://speech.ee.ntu.edu.tw/~tlkagk/index.html
图解深度学习_Grokking-Deep-Learninghttps://github.com/iamtrask/Grokking-Deep-Learning
《神经网络与深度学习》 Michael Nielsenhttps://github.com/Mikoto10032/DeepLearning/blob/master/books/%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C%E5%92%8C%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0neural%20networks%20and%20deep-learning-%E4%B8%AD%E6%96%87_ALL.pdf
CS321-Hintonhttp://www.cs.toronto.edu/~tijmen/csc321/
CS230: Deep Learninghttps://web.stanford.edu/class/cs230/
CS294-112http://rail.eecs.berkeley.edu/deeprlcourse/resources/
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#计算机视觉
CS231 李飞飞 已授权个人翻译笔记https://zhuanlan.zhihu.com/p/21930884
视频http://study.163.com/course/courseMain.htm?courseId=1003223001
计算机视觉研究方向https://mp.weixin.qq.com/s/WNkzfvYtEO5zJoe_-yAPow
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#自然语言处理
CS224n: Natural Language Processing with Deep Learninghttp://web.stanford.edu/class/cs224n/index.html
NLP上手教程https://github.com/FudanNLP/nlp-beginner
NLP入门推荐书目（2019版）https://zhuanlan.zhihu.com/p/58874484
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#深度强化学习
CS234: Reinforcement Learninghttp://web.stanford.edu/class/cs234/index.html
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#深入理解-1
《深度学习》 Yoshua Bengio.Ian GoodFellowhttps://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0.Yoshua%20Bengio%2BIan%20GoodFellow.pdf
《自然语言处理》Jacob Eisensteinhttps://github.com/Mikoto10032/DeepLearning/blob/master/books/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86.Jacob%20Eisenstein.pdf
《强化学习》https://github.com/Mikoto10032/DeepLearning/blob/master/books/Reinforcement%20Learning.Sutton.pdf
第二版http://incompleteideas.net/book/RLbook2018trimmed.pdf
hangdong的深度学习博客,论文推荐https://handong1587.github.io/categories.html#deep_learning-ref
Practical Deep Learning for Coders, v3https://course.fast.ai/
《Tensorflow实战Google深度学习框架》 郑泽宇 顾思宇https://github.com/Mikoto10032/DeepLearning/blob/master/books/Tensorflow%20%E5%AE%9E%E6%88%98Google%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E6%A1%86%E6%9E%B6.pdf
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#一些书单
2019年最新-深度学习、生成对抗、Pytorch优秀教材推荐https://zhuanlan.zhihu.com/p/63784033
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#工程能力
https://camo.githubusercontent.com/58d36614c20e3b9ef5ad2d43c9188de16ca86926eb15c478b42a364b628497c6/68747470733a2f2f706963342e7a68696d672e636f6d2f76322d30303930313332373836383866353230633037306232373931303235356362315f722e6a7067
LeetCodehttps://leetcode.com/
leetcode题解https://github.com/azl397985856/leetcode
《算法导论》中算法的C++实现https://github.com/huaxz1986/cplusplus-_Implementation_Of_Introduction_to_Algorithms
机器学习算法实战https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%AE%9E%E6%88%98%E7%AF%87
深度学习框架https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E6%A1%86%E6%9E%B6
如何成为一名算法工程师https://mp.weixin.qq.com/s/YMtnBAVDZepsMTO4h-VRtQ
从小白到入门算法，我的经验分享给你～https://mp.weixin.qq.com/s?__biz=MzAxMjcyNjE5MQ==&mid=2650488786&idx=1&sn=68b9536d0b0b3105ab8d79f8efcb0a4b&chksm=83a2e512b4d56c045c6ab0349108842e6a5b26e8f3e507ff5d19ee50e3bd63ef149a36d23eef&scene=0&xtrack=1&ascene=14&devicetype=android-28&version=27000437&nettype=WIFI&abtest_cookie=BAABAAoACwASABMABgAjlx4AVpkeANCZHgDcmR4A8ZkeAAOaHgAAAA%3D%3D&lang=zh_CN&pass_ticket=4yovfEr0v09yZCvvQ1NEy12qGIonnRpGi774X09Mh5EZD2oL%2BRz6FTtX9R5gALB1&wx_header=1
我的研究生这三年https://zhuanlan.zhihu.com/p/54161673
《AI算法工程师手册》http://www.huaxiaozhuan.com/
计算机相关技术面试必备https://github.com/CyC2018/CS-Notes
算法工程师面试https://github.com/imhuay/Algorithm_Interview_Notes-Chinese
深度学习面试题目https://github.com/ShanghaiTechAIClub/DLInterview
深度学习500问https://github.com/scutan90/DeepLearning-500-questions
AI算法岗求职攻略https://github.com/amusi/AI-Job-Notes#Strategy
Kaggle实战https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
Kaggle 项目实战（教程） = 文档 + 代码 + 视频https://github.com/apachecn/kaggle
Kaggle入门系列：（一）机器学习环境搭建https://zhuanlan.zhihu.com/p/29086448
Kaggle入门系列：（二）Kaggle简介https://zhuanlan.zhihu.com/p/29417603
Kaggle入门系列（三）Titanic初试身手https://zhuanlan.zhihu.com/p/29086614
从 0 到 1 走进 Kagglehttps://zhuanlan.zhihu.com/p/61660061
Kaggle 入门指南https://zhuanlan.zhihu.com/p/25742261
一个框架解决几乎所有机器学习问题https://zhuanlan.zhihu.com/p/61657532
Approaching (Almost) Any Machine Learning Problem | Abhishek Thakurhttp://blog.kaggle.com/2016/07/21/approaching-almost-any-machine-learning-problem-abhishek-thakur/
分分钟带你杀入Kaggle Top 1%https://zhuanlan.zhihu.com/p/27424282
如何达到Kaggle竞赛top 2%？这里有一篇特征探索经验帖https://zhuanlan.zhihu.com/p/48758045
如何在 Kaggle 首战中进入前 10%？https://zhuanlan.zhihu.com/p/27486736
大数据&机器学习相关竞赛推荐https://blog.csdn.net/weixin_33739541/article/details/87565983
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#二-神经网络模型概览
1. 一文看懂25个神经网络模型https://blog.csdn.net/qq_35082030/article/details/73368962
2. DNN概述论文：详解前馈、卷积和循环神经网络技术https://zhuanlan.zhihu.com/p/29141828
3. colah's bloghttp://colah.github.io/
4. Model Zoomhttps://modelzoo.co/
5. DNN概述https://zhuanlan.zhihu.com/p/29141828
6. 从基本原理到梯度下降，小白都能看懂的神经网络教程https://zhuanlan.zhihu.com/p/59385110
GitHub上的机器学习/深度学习综述项目合集https://zhuanlan.zhihu.com/p/60245227
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#cnn
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#发展史
1. 94页论文综述卷积神经网络：从基础技术到研究前景https://zhuanlan.zhihu.com/p/35388569
2. 从LeNet-5到DenseNethttps://zhuanlan.zhihu.com/p/31006686
3. CNN图像分割简史：从R-CNN到Mask R-CNN（译）https://zhuanlan.zhihu.com/p/26652657
4. 深度学习之目标检测的前世今生（Mask R-CNN）https://zhuanlan.zhihu.com/p/32830206
5. 纵览轻量化卷积神经网络：SqueezeNet、MobileNet、ShuffleNet、Xceptionhttps://zhuanlan.zhihu.com/p/32746221
6. 深度学习目标检测模型全面综述：Faster R-CNN、R-FCN和SSDhttps://zhuanlan.zhihu.com/p/29434605
7. 图像语义分割(Semantic segmentation) Surveyhttps://zhuanlan.zhihu.com/p/36801104
7. 从RCNN到SSD，这应该是最全的一份目标检测算法盘点https://zhuanlan.zhihu.com/p/36184131
8. 图像语义分割(Semantic segmentation) Surveyhttps://zhuanlan.zhihu.com/p/36801104
9. 语义分割 发展综述https://zhuanlan.zhihu.com/p/37618829
深度学习分类网络https://blog.csdn.net/PeaceInMind/article/details/78079263
CNN网络结构的发展https://zhuanlan.zhihu.com/p/68411179
卷积神经网络结构演变（form Hubel and Wiesel to SENet）https://zhuanlan.zhihu.com/p/34621135
从VGG到NASNet，一文概览图像分类网络https://zhuanlan.zhihu.com/p/35221368
From RCNN to YOLOhttps://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
上https://zhuanlan.zhihu.com/p/35724768
下https://zhuanlan.zhihu.com/p/35731743
后 R-CNN时代， Faster R-CNN、SSD、YOLO 各类变体统治下的目标检测综述：Faster R-CNN系列胜了吗？https://zhuanlan.zhihu.com/p/38709522
目标检测-20种模型的原味代码汇总https://zhuanlan.zhihu.com/p/37056927
目标检测算法综述三部曲https://zhuanlan.zhihu.com/p/40047760
基于深度学习的目标检测算法综述（一）https://zhuanlan.zhihu.com/p/40047760
基于深度学习的目标检测算法综述（二）https://zhuanlan.zhihu.com/p/40020809
基于深度学习的目标检测算法综述（三）https://zhuanlan.zhihu.com/p/40102001
如何走近深度学习人脸识别？你需要这篇超长综述 | 附开源代码https://zhuanlan.zhihu.com/p/35295839
人脸检测和识别算法综述https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
人脸检测算法综述 https://zhuanlan.zhihu.com/p/36621308
人脸检测背景介绍和发展现状https://zhuanlan.zhihu.com/p/32702868
人脸识别算法演化史https://zhuanlan.zhihu.com/p/36416906
CascadeCNNhttps://blog.csdn.net/shuzfan/article/details/50358809
MTCNNhttps://blog.csdn.net/qq_14845119/article/details/52680940
awesome-Face_Recognitionhttps://github.com/ChanChiChoi/awesome-Face_Recognition
异质人脸识别研究综述https://zhuanlan.zhihu.com/p/64191484
老板来了：人脸识别+手机推送，老板来了你立刻知道。https://zhuanlan.zhihu.com/p/26431250
手把手教你用Python实现人脸识别https://zhuanlan.zhihu.com/p/33456076
人脸识别项目，网络模型，损失函数，数据集相关总结https://www.jianshu.com/p/e57205edc364
基于深度学习的人脸识别技术综述https://zhuanlan.zhihu.com/p/24816781
如何走近深度学习人脸识别？你需要这篇超长综述https://zhuanlan.zhihu.com/p/35295839
人脸识别损失函数综述（附开源实现）https://zhuanlan.zhihu.com/p/51324547
深度学习图像超分辨率综述https://zhuanlan.zhihu.com/p/57564211
目标检测进化史https://zhuanlan.zhihu.com/p/60590369
一文看尽21篇目标检测最新论文（腾讯/Google/商汤/旷视/清华/浙大/CMU/华科/中科院等https://zhuanlan.zhihu.com/p/61080508
Anchor-Free目标检测算法https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
第一篇：arxiv2015_baidu_DenseBoxhttps://zhuanlan.zhihu.com/p/40221183
如何评价最新的anchor-free目标检测模型FoveaBox？https://www.zhihu.com/question/319605567/answer/647844997
FCOS: 最新的one-stage逐像素目标检测算法https://zhuanlan.zhihu.com/p/61644900
最新的Anchor-Free目标检测模型FCOS，现已开源！https://zhuanlan.zhihu.com/p/62198865
中科院牛津华为诺亚提出CenterNet，one-stage detector可达47AP，已开源！https://zhuanlan.zhihu.com/p/62789701
AnchorFreeDetectionhttps://github.com/VCBE123/AnchorFreeDetection
目标检测算法综述之FPN优化篇https://zhuanlan.zhihu.com/p/62975854
聊聊Anchor的"前世今生"（上）https://zhuanlan.zhihu.com/p/63273342
【CVPR2019正式公布】行人重识别论文https://zhuanlan.zhihu.com/p/62843442
2019 行人再识别年度进展回顾https://zhuanlan.zhihu.com/p/64004977
2019CVPR文本检测综述https://zhuanlan.zhihu.com/p/67319122
从SRCNN到EDSR，总结深度学习端到端超分辨率方法发展历程https://zhuanlan.zhihu.com/p/31664818
【CVPR2019正式公布】行人重识别论文https://zhuanlan.zhihu.com/p/62843442
自然场景文本检测识别技术综述https://mp.weixin.qq.com/s?__biz=MzU4MjQ3MDkwNA==&mid=2247485142&idx=1&sn=c0e01da30eb5e750be453eabe4be2bf4&chksm=fdb69b41cac11257ae22c7dac395e9651dab628fc35dd6d3c02d9566a8c7f5f2b56353d58a64&token=1065243837&lang=zh_CN#rd
Awesome-Image-Colorizationhttps://github.com/MarkMoHR/Awesome-Image-Colorization
Awesome-Edge-Detection-Papershttps://github.com/MarkMoHR/Awesome-Edge-Detection-Papers
OCR文字处理https://zhuanlan.zhihu.com/p/65707543
awesome-point-cloud-analysishttps://zhuanlan.zhihu.com/p/65690433
Graph Neural Network（GNN）综述https://zhuanlan.zhihu.com/p/65539782
小样本学习（Few-shot Learning）综述https://zhuanlan.zhihu.com/p/61215293
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#教程
卷积神经网络工作原理https://www.zhihu.com/question/39022858
A Comprehensive Introduction to Different Types of Convolutions in Deep Learninghttps://towardsdatascience.com/a-comprehensive-introduction-to-different-types-of-convolutions-in-deep-learning-669281e58215
上https://www.leiphone.com/news/201902/biIqSBpehsaXFwpN.html?uniqueCode=OTEsp9649VqJfUcO
下https://www.leiphone.com/news/201902/D2Mkv61w9IPq9qGh.html
变形卷积核、可分离卷积https://zhuanlan.zhihu.com/p/28749411
对深度可分离卷积、分组卷积、扩张卷积、转置卷积（反卷积）的理解https://blog.csdn.net/chaolei3/article/details/79374563
各种卷积https://www.cnblogs.com/cvtoEyes/p/8848815.html
卷积有多少种？一文读懂深度学习中的各种卷积https://zhuanlan.zhihu.com/p/57575810
反卷积https://buptldy.github.io/2016/10/29/2016-10-29-deconv/
Convolution Network及其变种（反卷积、扩展卷积、因果卷积、图卷积）https://www.cnblogs.com/yangperasd/p/7071657.html
如何评价最新的Octave Convolution？https://www.zhihu.com/question/320462422
深度学习基础--卷积类型https://zhuanlan.zhihu.com/p/59839551
Dilated/Atrous conv 空洞卷积/多孔卷积https://blog.csdn.net/silence2015/article/details/79748729
CNN模型之ShuffleNethttps://zhuanlan.zhihu.com/p/32304419
一文简述ResNet及其多种变体https://zhuanlan.zhihu.com/p/35985680
ResNet解析https://blog.csdn.net/lanran2/article/details/79057994
将CNN引入目标检测的开山之作：R-CNNhttps://zhuanlan.zhihu.com/p/23006190
深度学习（十八）基于R-CNN的物体检测https://blog.csdn.net/hjimce/article/details/50187029
R-CNN论文详解https://blog.csdn.net/u014696921/article/details/52824097
深度学习（六十四）Faster R-CNN物体检测https://blog.csdn.net/hjimce/article/details/73382553
先理解Mask R-CNN的工作原理，然后构建颜色填充器应用https://zhuanlan.zhihu.com/p/34816076
实例分割--Mask RCNN详解(ROI Align / Loss Function)https://www.codetd.com/article/2554465
语义分割卷积神经网络快速入门https://blog.csdn.net/qq_20084101/article/details/80455877
图像语义分割的工作原理和CNN架构变迁https://zhuanlan.zhihu.com/p/38033032
CapsNet入门系列http://mp.weixin.qq.com/s?__biz=MzI3ODkxODU3Mg==&mid=2247484099&idx=1&sn=97e209f1a9860c8d8c51e81d98fc8a0a&chksm=eb4ee600dc396f16624a33cdfc0ead905e62ae9447b49b20146020e6cbd7d71f089101512a40&scene=21#wechat_redirect
CapsNet入门系列之一：胶囊网络背后的直觉http://mp.weixin.qq.com/s?__biz=MzI3ODkxODU3Mg==&mid=2247484099&idx=1&sn=97e209f1a9860c8d8c51e81d98fc8a0a&chksm=eb4ee600dc396f16624a33cdfc0ead905e62ae9447b49b20146020e6cbd7d71f089101512a40&scene=21#wechat_redirect
CapsNet入门系列之二：胶囊如何工作http://mp.weixin.qq.com/s?__biz=MzI3ODkxODU3Mg==&mid=2247484165&idx=1&sn=0ca679e3a5f499f8d8addb405fe3df83&chksm=eb4ee7c6dc396ed0a330fcac12690110bcaf9a8a10794dbc5e1a326c69ecbb140140f55fd6ba&scene=21#wechat_redirect
CapsNet入门系列之三：囊间动态路由算法http://mp.weixin.qq.com/s?__biz=MzI3ODkxODU3Mg==&mid=2247484433&idx=1&sn=3afe4605bc2501eebbc41c6dd1af9572&chksm=eb4ee0d2dc3969c4619d6c1097d5c949c76c6c854e60d36eba4388da2c3855747818d062c90a&scene=21#wechat_redirect
CapsNet入门系列之四：胶囊网络架构https://mp.weixin.qq.com/s/6CRSen8P6zKaMGtX8IRfqw
YOLOhttp://www.mamicode.com/info-detail-2314392.html
目标检测|YOLOv2原理与实现(附YOLOv3)https://zhuanlan.zhihu.com/p/35325884?group_id=966229905398362112
目标检测模型YOLO v3问世https://zhuanlan.zhihu.com/p/34995629
Attentionhttp://www.cnblogs.com/shouhuxianjian/p/7903097.html
1https://zhuanlan.zhihu.com/p/31547842
2https://blog.csdn.net/yideqianfenzhiyi/article/details/79422857
3https://blog.csdn.net/Wayne2019/article/details/78488142
4https://zhuanlan.zhihu.com/p/37601161
5https://blog.csdn.net/bvl10101111/article/details/78470716
一文读懂卷积神经网络中的1x1卷积核https://zhuanlan.zhihu.com/p/40050371
目标检测之CornerNethttps://arxiv.org/abs/1808.01244
1https://zhuanlan.zhihu.com/p/41825737
2https://blog.csdn.net/Hibercraft/article/details/81637451
3https://zhuanlan.zhihu.com/p/41759548
人群计数http://chuansong.me/n/443237851736
1https://www.cnblogs.com/wmr95/p/8134692.html
2https://blog.csdn.net/u011285477/article/details/51954989
3https://blog.csdn.net/qingqingdeaini/article/details/79922549
RelationNetworkhttps://www.zhihu.com/question/60784169
ShuffleNet V2和四个网络架构设计准则https://zhuanlan.zhihu.com/p/40980942
【Tensorflow】tf.nn.depthwise_conv2d如何实现深度卷积?https://blog.csdn.net/mao_xiao_feng/article/details/78003476
Tensorflow】tf.nn.atrous_conv2d如何实现空洞卷积？https://blog.csdn.net/mao_xiao_feng/article/details/78003730
【Tensorflow】tf.nn.separable_conv2d如何实现深度可分卷积?https://blog.csdn.net/mao_xiao_feng/article/details/78002811
【TensorFlow】tf.nn.conv2d_transpose是怎样实现反卷积的？https://blog.csdn.net/mao_xiao_feng/article/details/71713358
何恺明大神的「Focal Loss」，如何更好地理解？https://zhuanlan.zhihu.com/p/32423092
CNN 模型所需的计算力（flops）和参数（parameters）数量是怎么计算的？https://www.zhihu.com/question/65305385
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#action
先读懂CapsNet架构然后用TensorFlow实现https://zhuanlan.zhihu.com/p/30753326
TensorFlow Object Detection API 教程https://blog.csdn.net/qq_36148847/article/details/79306762
TensorFlow 对象检测 API 教程1https://blog.csdn.net/qq_36148847/article/details/79306762
TensorFlow 对象检测 API 教程2https://blog.csdn.net/qq_36148847/article/details/79307598
TensorFlow 对象检测 API 教程3https://blog.csdn.net/qq_36148847/article/details/79307751
TensorFlow 对象检测 API 教程 4https://blog.csdn.net/qq_36148847/article/details/79307931
TensorFlow 对象检测 API 教程5https://blog.csdn.net/qq_36148847/article/details/79307933
在TensorFlow+Keras环境下使用RoI池化一步步实现注意力机制https://zhuanlan.zhihu.com/p/65327747
mxnet如何查看参数数量https://discuss.gluon.ai/t/topic/7216
mxnet查看FLOPShttps://github.com/likelyzhao/CalFLOPS-Mxnet
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#gan
苏剑林博客，讲解得淋漓尽致https://kexue.fm/category/Big-Data
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#发展史-1
千奇百怪的GAN变体https://zhuanlan.zhihu.com/p/26491601
The GAN Landscape：Losses, Architectures, Regularization, and Normalizationhttps://arxiv.org/pdf/1807.04720.pdf
深度学习新星：GAN的基本原理、应用和走向https://www.leiphone.com/news/201701/Kq6FvnjgbKK8Lh8N.html
GAN生成图像综述https://zhuanlan.zhihu.com/p/62746494
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#教程-1
1. GAN原理学习笔记https://zhuanlan.zhihu.com/p/27295635
2. 极端图像压缩的对抗生成网络https://zhuanlan.zhihu.com/p/35783437?group_id=969598777652420608
3. 台湾大学李宏毅GAN教程https://www.youtube.com/watch?v=0CKeqXl5IY0&feature=youtu.be
Basichttps://github.com/Mikoto10032/DeepLearning/blob/master/books/GAN-Basic%20Idea%20(2017.04.21).pdf
Improvinghttps://github.com/Mikoto10032/DeepLearning/blob/master/books/GAN-Improving%20GAN%20(2017.05.05).pdf
4. 2017年GAN 计算机视觉相关paper汇总https://zhuanlan.zhihu.com/p/29882709
5. 在Keras上实现GAN：构建消除图片模糊的应用https://zhuanlan.zhihu.com/p/35030377
6. CycleGAN：图片风格，想换就换 | ICCV 2017论文解读https://zhuanlan.zhihu.com/p/34711316
7. Wasserstein GANhttps://zhuanlan.zhihu.com/p/25071913
用变分推断统一理解生成模型（VAE、GAN、AAE、ALI）https://zhuanlan.zhihu.com/p/40105143
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#action-1
1. GAN学习指南：从原理入门到制作生成Demohttps://zhuanlan.zhihu.com/p/24767059
2. 机器之心GitHub项目：GAN完整理论推导与实现https://zhuanlan.zhihu.com/p/29837245
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#rnn
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#发展史-2
从90年代的SRNN开始，纵览循环神经网络27年的研究进展https://zhuanlan.zhihu.com/p/32668465
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#教程-2
完全图解RNN、RNN变体、Seq2Seq、Attention机制https://zhuanlan.zhihu.com/p/28054589
循环神经网络(RNN, Recurrent Neural Networks)介绍https://blog.csdn.net/heyongluoyao8/article/details/48636251
RNN以及LSTM的介绍和公式梳理https://blog.csdn.net/Dark_Scope/article/details/47056361
深度学习其五 循环神经网络https://zybuluo.com/hanbingtao/note/541458
用循环神经网络进行文件无损压缩：斯坦福大学提出DeepZiphttps://zhuanlan.zhihu.com/p/32582764
吴恩达序列建模课程https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
Coursera吴恩达《序列模型》课程笔记（1）-- 循环神经网络（RNN）https://zhuanlan.zhihu.com/p/34309635
Coursera吴恩达《序列模型》课程笔记（2）-- NLP & Word Embeddingshttps://zhuanlan.zhihu.com/p/34975871
Coursera吴恩达《序列模型》课程笔记（3）-- Sequence models & Attention mechanismhttps://zhuanlan.zhihu.com/p/35532553
Word2Vechttps://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
word2vec原理(一) CBOW与Skip-Gram模型基础https://www.cnblogs.com/pinard/p/7160330.html
word2vec原理(二) 基于Hierarchical Softmax的模型http://www.cnblogs.com/pinard/p/7243513.html
word2vec原理(三) 基于Negative Sampling的模型 http://www.cnblogs.com/pinard/p/7249903.html
用gensim学习word2vec http://www.cnblogs.com/pinard/p/7278324.html
聊聊 Transformerhttps://zhuanlan.zhihu.com/p/47812375
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#action-2
tensorflow中RNNcell源码分析以及自定义RNNCell的方法https://blog.csdn.net/liuchonge/article/details/78405185?locationNum=8&fps=1
TensorFlow中RNN实现的正确打开方式https://zhuanlan.zhihu.com/p/28196873
TensorFlow RNN 代码https://zhuanlan.zhihu.com/p/27906426
Tensorflow实现的深度NLP模型集锦https://zhuanlan.zhihu.com/p/67031035
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#lstm
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#教程-3
1. （译）理解长短期记忆(LSTM) 神经网络https://zhuanlan.zhihu.com/p/24018768
2. 一文读懂LSTM和RNNhttps://zhuanlan.zhihu.com/p/35878575?group_id=970350175025385472
3. 探索LSTM：基本概念到内部结构https://zhuanlan.zhihu.com/p/27345523
4. 翻译：深入理解LSTM系列https://blog.csdn.net/matrix_space/article/details/53374040
深入理解 LSTM 网络 (一)https://blog.csdn.net/matrix_space/article/details/53374040
深入理解 LSTM 网络 (二)https://blog.csdn.net/matrix_space/article/details/53376870
LSTMhttps://zhuanlan.zhihu.com/p/32085405
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#action-3
用tensorflow LSTM如何预测股票价格https://zhuanlan.zhihu.com/p/33186759
TensorFlow的多层LSTM实践https://zhuanlan.zhihu.com/p/29797089
《安娜卡列尼娜》文本生成——利用TensorFlow构建LSTM模型https://zhuanlan.zhihu.com/p/27087310
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#gnn
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#发展史-3
Graph Neural Network（GNN）综述https://zhuanlan.zhihu.com/p/65539782
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#教程-4
如何理解 Graph Convolutional Network（GCN）https://www.zhihu.com/question/54504471/answer/611222866
图卷积网络(Graph Convolutional networks, GCN) 简述https://zhuanlan.zhihu.com/p/38612863
图卷积网络(GCN)新手村完全指南https://zhuanlan.zhihu.com/p/54505069
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#action-4
图卷积网络到底怎么做，这是一份极简的Numpy实现https://zhuanlan.zhihu.com/p/57235377
DGLhttps://docs.dgl.ai/index.html
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#三-深度模型的优化--
1. 优化算法纵览http://fa.bianp.net/teaching/2018/eecs227at/
2. 从梯度下降到Adamhttps://zhuanlan.zhihu.com/p/27449596
3. 从梯度下降到拟牛顿法：盘点训练神经网络的五大学习算法https://zhuanlan.zhihu.com/p/25703402
4. 正则化技术总结https://zhuanlan.zhihu.com/p/35429054?group_id=966442942538444800
史上最全面的正则化技术总结与分析--part1https://zhuanlan.zhihu.com/p/35429054?group_id=966442942538444800
史上最全面的正则化技术总结与分析--part2https://zhuanlan.zhihu.com/p/35432128?group_id=966443101011738624
5. 最优化算法系列（math）https://blog.csdn.net/chunyun0716/article/category/6188191/2
6. 神经网络训练中的梯度消失与梯度爆炸https://zhuanlan.zhihu.com/p/25631496
7. 神经网络的优化及训练https://zhuanlan.zhihu.com/p/36050743
8. 通俗讲解查全率和查准率https://zhuanlan.zhihu.com/p/35888543
全面梳理：准确率,精确率,召回率,查准率,查全率,假阳性,真阳性,PRC,ROC,AUC,F1https://zhuanlan.zhihu.com/p/34079183
9. 激活函数一览https://zhuanlan.zhihu.com/p/30567264
10. Coursera吴恩达《优化深度神经网络》课程笔记（3）-- 超参数调试、Batch正则化和编程框架https://zhuanlan.zhihu.com/p/30922689
11. 机器学习各种熵https://zhuanlan.zhihu.com/p/35423404
12. 距离和相似性度量https://zhuanlan.zhihu.com/p/27305237
13. 机器学习里的黑色艺术：normalization, standardization, regularizationhttps://zhuanlan.zhihu.com/p/29974820
14. LSTM系列的梯度问题https://zhuanlan.zhihu.com/p/36101196
15. 损失函数整理https://zhuanlan.zhihu.com/p/35027284
16. 详解残差块为何有助于解决梯度弥散问题https://zhuanlan.zhihu.com/p/28124810
17. FAIR何恺明等人提出组归一化：替代批归一化，不受批量大小限制https://zhuanlan.zhihu.com/p/34858971
18. Batch Normalization（BN）https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
1 https://zhuanlan.zhihu.com/p/26702482
2 https://blog.csdn.net/hjimce/article/details/50866313
3 http://www.cvmart.net/community/article/detail/368
4 https://blog.csdn.net/edogawachia/article/details/80040456
5https://zhuanlan.zhihu.com/p/38176412
6https://www.zhihu.com/question/38102762
7https://zhuanlan.zhihu.com/p/52132614
19. 详解深度学习中的Normalization，不只是BNhttps://zhuanlan.zhihu.com/p/33173246
如何区分并记住常见的几种 Normalization 算法https://zhuanlan.zhihu.com/p/69659844
20. BFGShttps://blog.csdn.net/philosophyatmath/article/details/70173128
21. 详解深度学习中的梯度消失、爆炸原因及其解决方法https://zhuanlan.zhihu.com/p/33006526
22. Dropouthttps://arxiv.org/pdf/1207.0580.pdf
1https://blog.csdn.net/stdcoutzyx/article/details/49022443
2https://blog.csdn.net/hjimce/article/details/50413257
3https://blog.csdn.net/shuzfan/article/details/50580915
23.谱归一化（Spectral Normalization）的理解https://blog.csdn.net/StreamRock/article/details/83590347
常见向量范数和矩阵范数https://blog.csdn.net/left_la/article/details/9159949
谱范数正则（Spectral Norm Regularization）的理解https://blog.csdn.net/StreamRock/article/details/83539937
24.L1正则化与L2正则化https://zhuanlan.zhihu.com/p/35356992
25.为什么选用交叉熵而不是MSEhttps://zhuanlan.zhihu.com/p/61944055
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#四-炼丹术士那些事
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#调参经验
训练的神经网络不工作？一文带你跨过这37个坑https://blog.csdn.net/jiandanjinxin/article/details/77190687
神经网络训练trickhttps://zhuanlan.zhihu.com/p/59918821
深度学习与计算机视觉系列(8)_神经网络训练与注意点https://blog.csdn.net/han_xiaoyang/article/details/50521064
神经网络训练loss不下降原因集合https://blog.csdn.net/liuweiyuxiang/article/details/80856991
深度学习：欠拟合问题的几种解决方案https://blog.csdn.net/ningyanggege/article/details/82183666
过拟合和欠拟合问题https://blog.csdn.net/mzpmzk/article/details/79741682
机器学习：如何找到最优学习率https://blog.csdn.net/whut_ldz/article/details/78882871
实现https://github.com/L1aoXingyu/torchlib
不平衡数据集处理方法https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
其一https://machinelearningmastery.com/tactics-to-combat-imbalanced-classes-in-your-machine-learning-dataset/
其二https://www.zhihu.com/question/285824343
其三https://blog.csdn.net/songhk0209/article/details/71484469
同一个神经网络使用不同激活函数的表达能力是否一致https://www.zhihu.com/question/41841299
梯度下降优化算法纵览http://ruder.io/optimizing-gradient-descent/
1https://blog.csdn.net/qq_23269761/article/details/80901411
2https://www.cnblogs.com/guoyaohua/p/8542554.html
论文笔记之数据增广：mixuphttps://blog.csdn.net/ly244855983/article/details/78938667#%E8%AE%A8%E8%AE%BA
避坑指南：数据科学家新手常犯的13个错误https://zhuanlan.zhihu.com/p/44331706
凭什么相信CNN的结果?--可视化https://bindog.github.io/blog/2018/02/10/model-explanation/
凭什么相信你，我的CNN模型？（篇一：CAM和Grad-CAM)https://bindog.github.io/blog/2018/02/10/model-explanation/
凭什么相信你，我的CNN模型？（篇二：万金油LIME)http://bindog.github.io/blog/2018/02/11/model-explanation-2/
论文笔记:Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationhttps://www.jianshu.com/p/294ad9ae2e50
CV：基于Keras利用训练好的hdf5模型进行目标检测实现输出模型中的表情或性别的gradcam(可视化)https://blog.csdn.net/qq_41185868/article/details/80323646
大卷积核还是小卷积核?https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
1https://www.jianshu.com/p/d75375dd7ebd
2https://blog.csdn.net/kuangtun9713/article/details/79475457
模型可解释性差？你考虑了各种不确定性了吗？https://baijiahao.baidu.com/s?id=1608193373391996908
炼丹笔记系列https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
炼丹笔记一：样本不平衡问题https://zhuanlan.zhihu.com/p/56882616
炼丹笔记二：数据清洗https://zhuanlan.zhihu.com/p/56022212
炼丹笔记三：数据增强https://zhuanlan.zhihu.com/p/56139575
炼丹笔记四：小样本问题https://zhuanlan.zhihu.com/p/56365469
炼丹笔记五：数据标注https://zhuanlan.zhihu.com/p/56443169
炼丹笔记六 : 调参技巧https://zhuanlan.zhihu.com/p/56745640
炼丹笔记七：卷积神经网络模型设计https://zhuanlan.zhihu.com/p/57738934
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#刷排行榜的奇技淫巧
Kaggle 六大比赛最全面解析（上）https://www.leiphone.com/news/201803/XBjvQriKTyTMPLcz.html
Kaggle 六大比赛最全面解析（下）https://www.leiphone.com/news/201803/chz1DNHqgVWNEm5t.html
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#图像分类
炼丹笔记三：数据增强https://zhuanlan.zhihu.com/p/56139575
数据增强(Data Augmentation)https://zhuanlan.zhihu.com/p/41679153
【技术综述】 深度学习中的数据增强（上）https://zhuanlan.zhihu.com/p/38345420
【技术综述】深度学习中的数据增强（下）https://zhuanlan.zhihu.com/p/38437739
《Bag of Tricks for Image Classification with CNN》https://zhuanlan.zhihu.com/p/53324148
pdfhttps://arxiv.org/pdf/1812.01187.pdf
神经网络训练trickhttps://zhuanlan.zhihu.com/p/59918821
Kaggle解决方案分享https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
从0上手Kaggle图像分类挑战：冠军解决方案详解https://www.itcodemonkey.com/article/4898.html
Kaggle 冰山图像分类大赛近日落幕，看冠军团队方案有何亮点https://www.leiphone.com/news/201803/u40cjEZWArBfFaBm.html
【Kaggle冠军分享】图像识别和分类竞赛，数据增强及优化算法https://mp.weixin.qq.com/s/_S8EBBJ-u9g_fHp7I3ChMQ
识别座头鲸，Kaggle竞赛第一名解决方案解读https://zhuanlan.zhihu.com/p/58496385
kaggle 首战拿金牌总结https://zhuanlan.zhihu.com/p/60953933
16岁高中生夺冠Kaggle地标检索挑战赛！而且竟然是Kaggle老兵https://zhuanlan.zhihu.com/p/37522227
6次Kaggle计算机视觉类比赛赛后感https://zhuanlan.zhihu.com/p/37663895
Kaggle首战斩获第三-卫星图像识别https://zhuanlan.zhihu.com/p/63275166
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#目标检测
目标检测任务的优化策略trickshttps://zhuanlan.zhihu.com/p/56792817
目标检测小tricks--样本不均衡处理https://zhuanlan.zhihu.com/p/60612064
目标检测算法中的常见trickhttps://zhuanlan.zhihu.com/p/39262769
Kaggle：肺癌自动诊断系统3D Deep Leaky Noisy-or Network 论文阅读https://www.jianshu.com/p/50158f8daf0d
干货|大神教你如何参加kaggle比赛——根据CT扫描图预测肺癌https://yq.aliyun.com/articles/89312
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#五-年度总结
新年大礼包：机器之心2018高分教程合集https://zhuanlan.zhihu.com/p/53717510
CVPR2019目标检测方法进展综述https://zhuanlan.zhihu.com/p/59376548
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#六-科研相关
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#深度学习框架
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#python3x先修
The Python Tutorialhttps://docs.python.org/3/tutorial/
廖雪峰Python教程https://www.liaoxuefeng.com/wiki/0014316089557264a6b348958f449949df42a6d3a2e542c000
菜鸟教程http://www.runoob.com/python3/python3-tutorial.html
给深度学习入门者的Python快速教程 - 基础篇https://zhuanlan.zhihu.com/p/24162430
Python - 100天从新手到大师https://github.com/jackfrued/Python-100-Days
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#numpy先修
Quickstart tutorialhttps://www.numpy.org/devdocs/user/quickstart.html
Numpy快速入门(Numpy 1.14 官方文档中文翻译)https://www.jianshu.com/p/3e566f09a0cf
Numpy中文文档https://www.numpy.org.cn/index.html
给深度学习入门者的Python快速教程 - numpy和Matplotlib篇https://zhuanlan.zhihu.com/p/24309547
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#opencv-python
OpenCV-Python Tutorialshttps://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html
OpenCV官方教程中文版（For Python）https://www.cnblogs.com/Undo-self-blog/p/8423851.html
数字图像处理系列https://blog.csdn.net/feilong_csdn/article/category/8037591
python+OpenCV图像处理https://blog.csdn.net/qq_40962368/article/category/7688903
给深度学习入门者的Python快速教程 - 番外篇之Python-OpenCVhttps://zhuanlan.zhihu.com/p/24425116
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#pandas
Python 数据科学入门教程：Pandashttps://www.jianshu.com/p/d9774cf1fea5?utm_campaign=maleskine&utm_content=note&utm_medium=seo_notes&utm_source=recommendation
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#tensorflow
如何高效地学习 TensorFlow 代码https://www.zhihu.com/question/41667903
中文教程http://www.tensorfly.cn/tfdoc/tutorials/overview.html
TensorFlow官方文档https://www.w3cschool.cn/tensorflow_python/
CS20:Tensorflow for DeepLearning Researchhttp://web.stanford.edu/class/cs20si/syllabus.html
吴恩达TensorFlow专项课程https://zhuanlan.zhihu.com/p/62981537
【干货】史上最全的Tensorflow学习资源汇总https://zhuanlan.zhihu.com/p/35515805?group_id=967136289941897216
《21个项目玩转深度学习———基于TensorFlow的实践详解》https://github.com/hzy46/Deep-Learning-21-Examples
最全Tensorflow2.0 入门教程持续更新https://zhuanlan.zhihu.com/p/59507137
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#mxnet
Gluonhttp://zh.gluon.ai/#
GluonCVhttps://gluon-cv.mxnet.io/index.html
GluonNLPhttp://gluon-nlp.mxnet.io/
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#pytorch
PyTorch中文文档https://pytorch-cn.readthedocs.io/zh/latest/
WELCOME TO PYTORCH TUTORIALShttps://pytorch.org/tutorials/index.html
史上最全的PyTorch学习资源汇总https://zhuanlan.zhihu.com/p/64895011
【干货】史上最全的PyTorch学习资源汇总https://github.com/INTERMT/Awesome-PyTorch-Chinese
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#python可视化
Top 50 matplotlib Visualizations – The Master Plots (with full python code)https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/
Python之MatPlotLib使用教程https://www.jianshu.com/p/92e1a4497505
给深度学习入门者的Python快速教程 - numpy和Matplotlib篇https://zhuanlan.zhihu.com/p/24309547
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#标注工具
labelImghttps://github.com/tzutalin/labelImg
labelmehttps://github.com/wkentaro/labelme
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#数据集
1. 25个深度学习相关公开数据集https://zhuanlan.zhihu.com/p/35449783
2. 自然语言处理（NLP）数据集https://zhuanlan.zhihu.com/p/35423943
3.全唐诗(43030首)https://pan.baidu.com/s/1o7QlUhO
4. 伯克利大学公开数据集https://people.eecs.berkeley.edu/~taesung_park/
5. ACL 2018资源：100+ 预训练的中文词向量https://zhuanlan.zhihu.com/p/36835964
6. 预训练中文词向量https://github.com/Embedding/Chinese-Word-Vectors
7. 公开数据集种子库http://academictorrents.com
8. 计算机视觉，深度学习，数据挖掘数据集整理https://blog.csdn.net/c20081052/article/details/79814082
9. 计算机视觉著名数据集CV Datasetshttps://blog.csdn.net/accepthjp/article/details/51831026
10. 计算机视觉相关数据集和比赛https://blog.csdn.net/NNNNNNNNNNNNY/article/details/68485160
11. 这是一份非常全面的开源数据集，你，真的不想要吗？https://zhuanlan.zhihu.com/p/43846002
12. 人群密度估计现有主要数据集特点及其比较https://blog.csdn.net/weixin_40516558/article/details/81564464
13. DANBOORU2017: A LARGE-SCALE CROWDSOURCED AND TAGGED ANIME ILLUSTRATION DATASEThttps://www.gwern.net/Danbooru2017
14. 行人重识别数据集http://robustsystems.coe.neu.edu/sites/robustsystems.coe.neu.edu/files/systems/projectpages/reiddataset.html
15. 自然语言处理常见数据集、论文最全整理分享https://zhuanlan.zhihu.com/p/56144877
16. paper, code, sotahttps://paperswithcode.com/
17. 旷视RPC大型商品数据集发布！https://zhuanlan.zhihu.com/p/55627416
18. CVPR 2019「准满分」论文：英伟达推出首个跨摄像头汽车跟踪数据集(汽车Re-ID)https://zhuanlan.zhihu.com/p/60617001
19.【OCR技术】大批量生成文字训练集https://zhuanlan.zhihu.com/p/59052013
20. 语义分析数据集-MSRAhttps://github.com/msra-nlc/MSParS
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#会议列表
国际会议日期表https://github.com/JackieTseng/conference_call_for_paper
ai-deadlineshttps://github.com/abhshkdz/ai-deadlines/
Keep Up With New Trendshttps://handong1587.github.io/deep_learning/2017/12/18/keep-up-with-new-trends.html
计算机会议排名等级https://blog.csdn.net/cserchen/article/details/40508181
中国计算机学会(CCF)推荐国际学术刊物和会议https://www.ccf.org.cn/xspj/rgzn/
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#论文写作工具
Windows: Texlive+Texstudiohttps://jingyan.baidu.com/article/b2c186c83c9b40c46ff6ff4f.html
Ubuntu: Texlive+Texmakerhttps://jingyan.baidu.com/article/7c6fb4280b024180642c90e4.html
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#论文画图工具
Matplotlibhttps://patch-diff.githubusercontent.com/mppcasc/DeepLearning#Python%E5%8F%AF%E8%A7%86%E5%8C%96
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#论文写作教程
刘知远_如何写一篇合格的NLP论文https://zhuanlan.zhihu.com/p/58752815
刘洋_如何写论文_V7http://nlp.csai.tsinghua.edu.cn/~ly/talks/cwmt14_tut.pdf
如何端到端地写科研论文-邱锡鹏https://xpqiu.github.io/slides/20181019-PaperWriting.pdf
论文Introduction写作其一https://zhuanlan.zhihu.com/p/33876355
论文Introduction写作其二https://zhuanlan.zhihu.com/p/52494933
论文Introduction写作其三https://zhuanlan.zhihu.com/p/52494879
毕业论文怎么写https://zhuanlan.zhihu.com/c_179195484
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#researchgo
ResearchGo:研究生活第一帖——文献检索与管理https://zhuanlan.zhihu.com/p/22323250?refer=wjdml
ResearchGo:研究生活第二贴——文献阅读https://zhuanlan.zhihu.com/p/22402393?refer=wjdml
ResearchGo:研究生活第三帖——阅读辅助https://zhuanlan.zhihu.com/p/22622502?refer=wjdml
ResearchGo:研究生活第四帖——文献调研https://zhuanlan.zhihu.com/p/23178836?refer=wjdml
ResearchGo:研究生活第五帖——文献综述https://zhuanlan.zhihu.com/p/23356843?refer=wjdml
ResearchGo:研究生活第六帖——如何讲论文https://zhuanlan.zhihu.com/p/23872063?refer=wjdml
ResearchGo:研究生活第七帖——专利检索与申请https://zhuanlan.zhihu.com/p/25191025
ResearchGo:研究生活第八帖——写论文、做PPT、写文档必备工具集锦https://zhuanlan.zhihu.com/p/62100815
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#毕业论文排版
吐血推荐收藏的学位论文排版教程（完整版）https://zhuanlan.zhihu.com/p/52495345
论文怎么写——如何修改毕业论文格式https://zhuanlan.zhihu.com/p/35951260
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#机器学习深度学习基础理论
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#信息论
1. 机器学习中的各种熵https://zhuanlan.zhihu.com/p/35423404
2. 从香农熵到手推KL散度：纵览机器学习中的信息论https://zhuanlan.zhihu.com/p/32985487
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#深度学习一些研究领域
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#多任务学习
模型汇总-14 多任务学习-Multitask Learning概述https://zhuanlan.zhihu.com/p/27421983
(译)深度神经网络的多任务学习概览(An Overview of Multi-task Learning in Deep Neural Networks)http://www.cnblogs.com/shuzirank/p/7141017.html
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#零次学习zero-shot-learning
零次学习（Zero-Shot Learning）入门https://zhuanlan.zhihu.com/p/34656727
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#多视觉学习multi-view-learning
Multi-view Learning 多视角学习入门https://blog.csdn.net/danliwoo/article/details/79278574
多视角学习 (Multi-View Learning)https://blog.csdn.net/shine19930820/article/details/77426599
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#embedding
万物皆Embedding，从经典的word2vec到深度学习基本操作item2vechttps://zhuanlan.zhihu.com/p/53194407
YJango的Word Embedding--介绍https://zhuanlan.zhihu.com/p/27830489
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#word2vec
NLP 秒懂词向量Word2vec的本质https://zhuanlan.zhihu.com/p/26306795
一篇通俗易懂的word2vechttps://zhuanlan.zhihu.com/p/35500923
YJango的Word Embedding--介绍https://zhuanlan.zhihu.com/p/27830489
nlp中的词向量对比：word2vec/glove/fastText/elmo/GPT/berthttps://zhuanlan.zhihu.com/p/56382372
词嵌入（word2vec）https://zh.diveintodeeplearning.org/chapter_natural-language-processing/word2vec.html
谈谈谷歌word2vec的原理https://blog.csdn.net/wangyangzhizhou/article/details/77073023
Word2Vec中为什么使用负采样？https://zhuanlan.zhihu.com/p/67117737
练习-word2vechttps://zhuanlan.zhihu.com/p/29200034
word2vec方法的实现和应用https://zhuanlan.zhihu.com/p/31886824
自然语言处理入门 word2vec 使用tensorflow自己训练词向量https://blog.csdn.net/wzdjsgf/article/details/79541492
使用tensorflow实现word2vec中文词向量的训练https://zhuanlan.zhihu.com/p/28979653
如何用TensorFlow训练词向量https://blog.csdn.net/wangyangzhizhou/article/details/77530479?locationNum=1&fps=1
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#迁移学习
1. 迁移学习：经典算法解析https://blog.csdn.net/linolzhang/article/details/73358219
2. 什么是迁移学习 (Transfer Learning)？这个领域历史发展前景如何？https://www.zhihu.com/question/41979241
3. 迁移学习个人笔记https://github.com/Mikoto10032/DeepLearning/blob/master/notes/%E6%97%A5%E5%B8%B8%E9%98%85%E8%AF%BB%E7%AC%94%E8%AE%B0/2018_4_12_%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0.pdf
迁移学习总结(One Shot Learning, Zero Shot Learning)https://blog.csdn.net/XJTU_NOC_Wei/article/details/77850221
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#域自适应
Domain Adaptation视频教程（附PPT）及经典论文分享https://zhuanlan.zhihu.com/p/27519182
模型汇总15 领域适应性Domain Adaptation、One-shot/zero-shot Learning概述https://zhuanlan.zhihu.com/p/27449079
【深度学习】论文导读：无监督域适应（Deep Transfer Network: Unsupervised Domain Adaptation）https://blog.csdn.net/mao_xiao_feng/article/details/54426101
【论文阅读笔记】基于反向传播的无监督域自适应研究https://zhuanlan.zhihu.com/p/37298073
【Valse大会首发】领域自适应及其在人脸识别中的应用https://zhuanlan.zhihu.com/p/21441807
CVPR 2018：基于域适应弱监督学习的目标检测https://zhuanlan.zhihu.com/p/41126114
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#元学习
OpenAI提出新型元学习方法EPG，调整损失函数实现新任务上的快速训练https://zhuanlan.zhihu.com/p/35869158?group_id=970310501209645056
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#强化学习
强化学习（Reinforcement Learning）知识整理https://zhuanlan.zhihu.com/p/25498081
强化学习从入门到放弃的资料https://zhuanlan.zhihu.com/p/34918639
强化学习入门https://zhuanlan.zhihu.com/p/25498081
强化学习入门 第一讲 MDPhttps://zhuanlan.zhihu.com/p/25498081
强化学习——从Q-Learning到DQN到底发生了什么？https://zhuanlan.zhihu.com/p/35882937
从强化学习到深度强化学习（上）https://zhuanlan.zhihu.com/p/35688924
从强化学习到深度强化学习（下）https://zhuanlan.zhihu.com/p/35965070
一文带你理解Q-Learning的搜索策略https://zhuanlan.zhihu.com/p/37048004
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#推荐系统
推荐算法相关的文档整理https://zhuanlan.zhihu.com/p/29969721
Embedding从入门到专家必读的十篇论文https://zhuanlan.zhihu.com/p/58805184
推荐系统之路 (1)：走上推荐系统这条路https://mp.weixin.qq.com/s?__biz=MzA3MzI4MjgzMw==&mid=2650760136&idx=2&sn=afc75d6bf614bc7929b6ea9cb1abb260&chksm=871aa7b6b06d2ea0129ec7b06bf7b2448c3a55d485d6b80a066d622709066242fe7c925160c3&scene=21#wechat_redirect
推荐系统之路 (2)：产品聚类https://zhuanlan.zhihu.com/p/64722876
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#自然语言处理nlp
基于word2vec训练词向量(一)https://zhuanlan.zhihu.com/p/35648927
基于word2vec训练词向量(二)https://zhuanlan.zhihu.com/p/35889385
自然语言处理中的自注意力机制（Self-Attention Mechanism）https://zhuanlan.zhihu.com/p/35041012
自然语言处理中注意力机制综述https://zhuanlan.zhihu.com/p/54491016
YJango的Word Embedding--介绍https://zhuanlan.zhihu.com/p/27830489
CMU&谷歌大脑提出新型问答模型QANethttps://zhuanlan.zhihu.com/p/37168143
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#语义分割相关算法
干货 | 一文概览主要语义分割网络https://blog.csdn.net/qq_20084101/article/details/80432960
深度学习中IU、IoU(Intersection over Union)https://blog.csdn.net/iamoldpan/article/details/78799857
Selective Search for Object Detection https://www.learnopencv.com/selective-search-for-object-detection-cpp-python/
（译文）https://blog.csdn.net/guoyunfei20/article/details/78723646
NMS——非极大值抑制https://blog.csdn.net/shuzfan/article/details/52711706
边框回归(Bounding Box Regression)详解https://blog.csdn.net/zijin0802034/article/details/77685438
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#机器学习理论与实战
机器学习原理https://github.com/shunliz/Machine-Learning
ID3、C4.5、CART、随机森林、bagging、boosting、Adaboost、GBDT、xgboost算法总结https://zhuanlan.zhihu.com/p/34534004
数据挖掘十大算法简要说明http://www.cnblogs.com/en-heng/p/5013995.html
AdaBoost到GBDT系列https://patch-diff.githubusercontent.com/mppcasc/DeepLearning/blob/master
当我们在谈论GBDT：从 AdaBoost 到 Gradient Boostinghttps://zhuanlan.zhihu.com/p/25096501?refer=data-miner
当我们在谈论GBDT：Gradient Boosting 用于分类与回归https://zhuanlan.zhihu.com/p/25257856?refer=data-miner
当我们在谈论GBDT：其他 Ensemble Learning 算法https://zhuanlan.zhihu.com/p/25443980
集成学习之bagging,stacking,boosting概念理解https://zhuanlan.zhihu.com/p/41809927
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#机器学习理论篇
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#逻辑回归
【机器学习面试题】逻辑回归篇https://zhuanlan.zhihu.com/p/62653034
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#决策树decision-tree
Python3《机器学习实战》学习笔记（二）：决策树基础篇之让我们从相亲说起https://blog.csdn.net/c406495762/article/details/75663451
Python3《机器学习实战》学习笔记（三）：决策树实战篇之为自己配个隐形眼镜https://blog.csdn.net/c406495762/article/details/76262487
机器学习实战教程（十三）：树回归基础篇之CART算法与树剪枝http://cuijiahua.com/blog/2017/12/ml_13_regtree_1.html
《机器学习实战》基于信息论的三种决策树算法(ID3,C4.5,CART)https://blog.csdn.net/gamer_gyt/article/details/51242815
说说决策树剪枝算法https://zhuanlan.zhihu.com/p/31404571
机器学习实战 第九章 树回归https://blog.csdn.net/namelessml/article/details/52595066
决策树值ID3、C4.5实现https://blog.csdn.net/u014688145/article/details/53212112
决策树值CART实现https://blog.csdn.net/u014688145/article/details/53326910
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#随机森林
随机森林（Random Forest）入门与实战https://blog.csdn.net/sb19931201/article/details/52601058
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#支持向量机svm--
SVM通俗导论 July（本文章是我看过最好的SVM导论）https://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA%E9%80%9A%E4%BF%97%E5%AF%BC%E8%AE%BA%EF%BC%88%E7%90%86%E8%A7%A3SVM%E7%9A%84%E4%B8%89%E5%B1%82%E5%A2%83%E7%95%8C%EF%BC%89LaTeX%E6%9C%80%E6%96%B0%E7%89%88_2015.1.9.pdf
Python3《机器学习实战》学习笔记（八）：支持向量机原理篇之手撕线性SVM （SMO训练过程总结得清晰易懂）https://blog.csdn.net/c406495762/article/details/78072313
svm核函数的理解和选择https://blog.csdn.net/leonis_v/article/details/50688766
核函数和径向基核函数 (Radial Basis Function)--RBFhttps://blog.csdn.net/huang1024rui/article/details/51510611
SVM核函数https://blog.csdn.net/xiaowei_cqu/article/details/35993729
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#pca
主成分分析（PCA）原理详解https://blog.csdn.net/program_developer/article/details/80632779
图文并茂的PCA教程https://blog.csdn.net/hustqb/article/details/78394058
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#svd
1. 关于奇异值分解SVD的总结（PCA、LDI）https://zhuanlan.zhihu.com/p/30482640
2. 奇异值分解（SVD）https://zhuanlan.zhihu.com/p/29846048
3. 奇异值分解(SVD)原理详解及推导https://blog.csdn.net/zhongkejingwang/article/details/43053513
4. SVD在推荐系统中的应用详解以及算法推导https://blog.csdn.net/zhongkejingwang/article/details/43083603
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#lda
教科书上的LDA为什么长这个样子？https://zhuanlan.zhihu.com/p/42238953
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#标签传播算法label-propagation-algorithm--
标签传播算法（Label Propagation）及Python实现https://blog.csdn.net/zouxy09/article/details/49105265
参考资料https://github.com/Mikoto10032/DeepLearning/blob/master/books/Semi-Supervised%20Learning%20with%20Graphs.pdf
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#蒙塔卡罗搜索树
蒙特卡洛树搜索入门指南https://zhuanlan.zhihu.com/p/34950988
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#马尔科夫决策
马尔科夫决策过程之Markov Processes（马尔科夫过程）https://zhuanlan.zhihu.com/p/35124726
马尔科夫决策过程之Markov Reward Process（马尔科夫奖励过程）https://zhuanlan.zhihu.com/p/35231424
马尔科夫决策过程之Bellman Equation（贝尔曼方程）https://zhuanlan.zhihu.com/p/35261164
马尔科夫决策过程之Markov Decision Process(马尔科夫决策过程)https://zhuanlan.zhihu.com/p/35354956
马尔科夫决策过程之最优价值函数与最优策略https://zhuanlan.zhihu.com/p/35373905
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#gbdt
LightGBM大战XGBoosthttps://zhuanlan.zhihu.com/p/35645973
概述XGBoost、Light GBM和CatBoost的同与不同https://zhuanlan.zhihu.com/p/34698733
梯度提升决策树https://zhuanlan.zhihu.com/p/36339161
GBDT原理及应用https://zhuanlan.zhihu.com/p/30339807
XGBOOST原理篇https://zhuanlan.zhihu.com/p/31654000
xgboost入门与实战（原理篇）https://blog.csdn.net/sb19931201/article/details/52557382
xgboost入门与实战（实战调参篇）https://blog.csdn.net/sb19931201/article/details/52577592
【干货合集】通俗理解kaggle比赛大杀器xgboosthttps://zhuanlan.zhihu.com/p/41417638
GBDT分类的原理及Python实现https://blog.csdn.net/bf02jgtrs00xktcx/article/details/82719765
GBDT原理及利用GBDT构造新的特征-Python实现https://blog.csdn.net/shine19930820/article/details/71713680
Python+GBDT算法实战——预测实现100%准确率https://www.jianshu.com/p/47e73a985ba1
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#集成ensemble
集成学习法之bagging方法和boosting方法https://blog.csdn.net/qq_30189255/article/details/51532442
Bagging,Boosting,Stackinghttps://blog.csdn.net/Mr_tyting/article/details/72957853
常用的模型集成方法介绍：bagging、boosting 、stackinghttps://zhuanlan.zhihu.com/p/65888174
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#em期望最大化
人人都懂的EM算法 https://zhuanlan.zhihu.com/p/36331115
EM算法入门文章https://zhuanlan.zhihu.com/p/61768577
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#条件随机场crf-判别式模型
如何轻松愉快地理解条件随机场https://www.jianshu.com/p/55755fc649b1
如何用简单易懂的例子解释条件随机场（CRF）模型？它和HMM有什么区别？https://www.zhihu.com/question/35866596
HMM ,MHMM,CRF 优缺点与区别https://blog.csdn.net/u013378306/article/details/55213029
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#tsne
流形学习-高维数据的降维与可视化https://blog.csdn.net/u012162613/article/details/45920827
tSNEhttps://blog.csdn.net/flyingzhan/article/details/79521765
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#谱聚类
谱聚类（Spectral Clustering）算法介绍https://blog.csdn.net/qq_24519677/article/details/82291867
聚类5--谱和谱聚类https://blog.csdn.net/xueyingxue001/article/details/51966980
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#异常点检测
数据挖掘中常见的「异常检测」算法有哪些？https://www.zhihu.com/question/280696035/answer/417091151
异常点检测算法综述https://zhuanlan.zhihu.com/p/30169110
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#降维算法
数据降维算法-从PCA到LargeVishttps://zhuanlan.zhihu.com/p/62470700
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#机器学习实战篇
15分钟带你入门sklearn与机器学习——分类算法篇https://mp.weixin.qq.com/s?__biz=Mzg5NzAxMDgwNg==&mid=2247484110&idx=1&sn=b016e270d7b7707e6ad41a81ca45fc28&chksm=c0791fd7f70e96c103a8a2aebee166ce14f5648b3b889dd85dd9786f48b6b8269f11e5e27e1c&scene=21#wechat_redirect
如何为你的回归问题选择最合适的机器学习方法？https://zhuanlan.zhihu.com/p/62034592
十分钟上手sklearn：安装，获取数据，数据预处理http://blackblog.tech/2018/02/05/%E5%8D%81%E5%88%86%E9%92%9F%E4%B8%8A%E6%89%8Bsklearn-1/
十分钟上手sklearn：特征提取，常用模型，交叉验证http://blackblog.tech/2018/02/05/%E5%8D%81%E5%88%86%E9%92%9F%E4%B8%8A%E6%89%8Bsklearn-2/
Machine Learning Course with Pythonhttps://github.com/machinelearningmindset/machine-learning-course
Python3机器学习https://blog.csdn.net/c406495762/column/info/16415
https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#生活使我健步如飞jpg
排行榜的奇技淫巧https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#%E5%88%B7%E6%8E%92%E8%A1%8C%E6%A6%9C%E7%9A%84%E5%A5%87%E6%8A%80%E6%B7%AB%E5%B7%A7
Readme https://patch-diff.githubusercontent.com/mppcasc/DeepLearning#readme-ov-file
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