本文给大家推荐一个深度学习（Deep Learning）的最全资料项目：awesome-deep-learning。

Awesome Deep Learning

该项目主要包含以下内容：

免费在线书籍

1. Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Courville (05/07/2015)
2. Neural Networks and Deep Learning by Michael Nielsen (Dec 2014)
3. Deep Learning by Microsoft Research (2013)
4. Deep Learning Tutorial by LISA lab, University of Montreal (Jan 6 2015)
5. neuraltalk by Andrej Karpathy : numpy-based RNN/LSTM implementation
6. An introduction to genetic algorithms
7. Artificial Intelligence: A Modern Approach
8. Deep Learning in Neural Networks: An Overview
9. Artificial intelligence and machine learning: Topic wise explanation

1. Machine Learning - Stanford by Andrew Ng in Coursera (2010-2014)
2. Machine Learning - Caltech by Yaser Abu-Mostafa (2012-2014)
3. Machine Learning - Carnegie Mellon by Tom Mitchell (Spring 2011)
4. Neural Networks for Machine Learning by Geoffrey Hinton in Coursera (2012)
5. Neural networks class by Hugo Larochelle from Université de Sherbrooke (2013)
6. Deep Learning Course by CILVR lab @ NYU (2014)
7. A.I - Berkeley by Dan Klein and Pieter Abbeel (2013)
8. A.I - MIT by Patrick Henry Winston (2010)
9. Vision and learning - computers and brains by Shimon Ullman, Tomaso Poggio, Ethan Meyers @ MIT (2013)
10. Convolutional Neural Networks for Visual Recognition - Stanford by Fei-Fei Li, Andrej Karpathy (2017)
11. Deep Learning for Natural Language Processing - Stanford
12. Neural Networks - usherbrooke
13. Machine Learning - Oxford (2014-2015)
14. Deep Learning - Nvidia (2015)
15. Graduate Summer School: Deep Learning, Feature Learning by Geoffrey Hinton, Yoshua Bengio, Yann LeCun, Andrew Ng, Nando de Freitas and several others @ IPAM, UCLA (2012)
16. Deep Learning - Udacity/Google by Vincent Vanhoucke and Arpan Chakraborty (2016)
17. Deep Learning - UWaterloo by Prof. Ali Ghodsi at University of Waterloo (2015)
18. Statistical Machine Learning - CMU by Prof. Larry Wasserman
19. Deep Learning Course by Yann LeCun (2016)
20. Designing, Visualizing and Understanding Deep Neural Networks-UC Berkeley
21. UVA Deep Learning Course MSc in Artificial Intelligence for the University of Amsterdam.
22. MIT 6.S094: Deep Learning for Self-Driving Cars
23. MIT 6.S191: Introduction to Deep Learning
24. Berkeley CS 294: Deep Reinforcement Learning
25. Keras in Motion video course
26. Practical Deep Learning For Coders by Jeremy Howard - Fast.ai
27. Introduction to Deep Learning by Prof. Bhiksha Raj (2017)
28. AI for Everyone by Andrew Ng (2019)
29. MIT Intro to Deep Learning 7 day bootcamp - A seven day bootcamp designed in MIT to introduce deep learning methods and applications (2019)
30. Deep Blueberry: Deep Learning - A free five-weekend plan to self-learners to learn the basics of deep-learning architectures like CNNs, LSTMs, RNNs, VAEs, GANs, DQN, A3C and more (2019)
31. Spinning Up in Deep Reinforcement Learning - A free deep reinforcement learning course by OpenAI (2019)

视频和讲座

共计19个视频或讲座，都来自深度学习领域的大牛，比如吴恩达、Yann LeCun、Toshua bengio、Hinton。

1. How To Create A Mind By Ray Kurzweil
2. Deep Learning, Self-Taught Learning and Unsupervised Feature Learning By Andrew Ng
3. Recent Developments in Deep Learning By Geoff Hinton
4. The Unreasonable Effectiveness of Deep Learning by Yann LeCun
5. Deep Learning of Representations by Yoshua bengio
6. Principles of Hierarchical Temporal Memory by Jeff Hawkins
7. Machine Learning Discussion Group - Deep Learning w/ Stanford AI Lab by Adam Coates
8. Making Sense of the World with Deep Learning By Adam Coates
9. Demystifying Unsupervised Feature Learning By Adam Coates
10. Visual Perception with Deep Learning By Yann LeCun
11. The Next Generation of Neural Networks By Geoffrey Hinton at GoogleTechTalks
12. The wonderful and terrifying implications of computers that can learn By Jeremy Howard at TEDxBrussels
13. Unsupervised Deep Learning - Stanford by Andrew Ng in Stanford (2011)
14. Natural Language Processing By Chris Manning in Stanford
15. A beginners Guide to Deep Neural Networks By Natalie Hammel and Lorraine Yurshansky
16. Deep Learning: Intelligence from Big Data by Steve Jurvetson (and panel) at VLAB in Stanford.
17. Introduction to Artificial Neural Networks and Deep Learning by Leo Isikdogan at Motorola Mobility HQ
18. NIPS 2016 lecture and workshop videos - NIPS 2016
19. Deep Learning Crash Course: a series of mini-lectures by Leo Isikdogan on YouTube (2018)

共计42篇论文，都是深度学习中经典的必读论文，比如LSTM、GRU、反向传播、Batch Normaliation等。

You can also find the most cited deep learning papers from here

共计23篇深度学习相关教程，其中涉及神经网络、自然语言处理和常见深度学习框架（TensorFlow/PyTorch/Keras）等。

共计99位业界学者，都是深度学习领域的大牛，比如Hinton、吴恩达、李飞飞和Ian Goodfellow等。

共计27个深度学习资源网站，比如AI Weekly和Deep Learning News。

共计121个数据集，比如MNIST、CIFAR、ImageNet、COCO和UCID等。

1. MNIST Handwritten digits
2. Google House Numbers from street view
3. CIFAR-10 and CIFAR-100
4. IMAGENET
5. Tiny Images 80 Million tiny images6.
6. Flickr Data 100 Million Yahoo dataset
7. Berkeley Segmentation Dataset 500
8. UC Irvine Machine Learning Repository
9. Flickr 8k
10. Flickr 30k
11. Microsoft COCO
12. VQA
13. Image QA
14. AT&T Laboratories Cambridge face database
15. AVHRR Pathfinder
16. Air Freight - The Air Freight data set is a ray-traced image sequence along with ground truth segmentation based on textural characteristics. (455 images + GT, each 160x120 pixels). (Formats: PNG)
17. Amsterdam Library of Object Images - ALOI is a color image collection of one-thousand small objects, recorded for scientific purposes. In order to capture the sensory variation in object recordings, we systematically varied viewing angle, illumination angle, and illumination color for each object, and additionally captured wide-baseline stereo images. We recorded over a hundred images of each object, yielding a total of 110,250 images for the collection. (Formats: png)
18. Annotated face, hand, cardiac & meat images - Most images & annotations are supplemented by various ASM/AAM analyses using the AAM-API. (Formats: bmp,asf)
19. Image Analysis and Computer Graphics
20. Brown University Stimuli - A variety of datasets including geons, objects, and "greebles". Good for testing recognition algorithms. (Formats: pict)
21. CAVIAR video sequences of mall and public space behavior - 90K video frames in 90 sequences of various human activities, with XML ground truth of detection and behavior classification (Formats: MPEG2 & JPEG)
22. Machine Vision Unit
23. CCITT Fax standard images - 8 images (Formats: gif)
24. CMU CIL's Stereo Data with Ground Truth - 3 sets of 11 images, including color tiff images with spectroradiometry (Formats: gif, tiff)
25. CMU PIE Database - A database of 41,368 face images of 68 people captured under 13 poses, 43 illuminations conditions, and with 4 different expressions.
26. CMU VASC Image Database - Images, sequences, stereo pairs (thousands of images) (Formats: Sun Rasterimage)
27. Caltech Image Database - about 20 images - mostly top-down views of small objects and toys. (Formats: GIF)
28. Columbia-Utrecht Reflectance and Texture Database - Texture and reflectance measurements for over 60 samples of 3D texture, observed with over 200 different combinations of viewing and illumination directions. (Formats: bmp)
29. Computational Colour Constancy Data - A dataset oriented towards computational color constancy, but useful for computer vision in general. It includes synthetic data, camera sensor data, and over 700 images. (Formats: tiff)
30. Computational Vision Lab
31. Content-based image retrieval database - 11 sets of color images for testing algorithms for content-based retrieval. Most sets have a description file with names of objects in each image. (Formats: jpg)
32. Efficient Content-based Retrieval Group
33. Densely Sampled View Spheres - Densely sampled view spheres - upper half of the view sphere of two toy objects with 2500 images each. (Formats: tiff)
34. Computer Science VII (Graphical Systems)
35. Digital Embryos - Digital embryos are novel objects which may be used to develop and test object recognition systems. They have an organic appearance. (Formats: various formats are available on request)
36. Univerity of Minnesota Vision Lab
37. El Salvador Atlas of Gastrointestinal VideoEndoscopy - Images and Videos of his-res of studies taken from Gastrointestinal Video endoscopy. (Formats: jpg, mpg, gif)
38. FG-NET Facial Aging Database - Database contains 1002 face images showing subjects at different ages. (Formats: jpg)
39. FVC2000 Fingerprint Databases - FVC2000 is the First International Competition for Fingerprint Verification Algorithms. Four fingerprint databases constitute the FVC2000 benchmark (3520 fingerprints in all).
40. Biometric Systems Lab - University of Bologna
41. Face and Gesture images and image sequences - Several image datasets of faces and gestures that are ground truth annotated for benchmarking
42. German Fingerspelling Database - The database contains 35 gestures and consists of 1400 image sequences that contain gestures of 20 different persons recorded under non-uniform daylight lighting conditions. (Formats: mpg,jpg)
43. Language Processing and Pattern Recognition
44. Groningen Natural Image Database - 4000+ 1536x1024 (16 bit) calibrated outdoor images (Formats: homebrew)
45. ICG Testhouse sequence - 2 turntable sequences from ifferent viewing heights, 36 images each, resolution 1000x750, color (Formats: PPM)
46. Institute of Computer Graphics and Vision
47. IEN Image Library - 1000+ images, mostly outdoor sequences (Formats: raw, ppm)
48. INRIA's Syntim images database - 15 color image of simple objects (Formats: gif)
49. INRIA
50. INRIA's Syntim stereo databases - 34 calibrated color stereo pairs (Formats: gif)
51. Image Analysis Laboratory - Images obtained from a variety of imaging modalities -- raw CFA images, range images and a host of "medical images". (Formats: homebrew)
52. Image Analysis Laboratory
53. Image Database - An image database including some textures
54. JAFFE Facial Expression Image Database - The JAFFE database consists of 213 images of Japanese female subjects posing 6 basic facial expressions as well as a neutral pose. Ratings on emotion adjectives are also available, free of charge, for research purposes. (Formats: TIFF Grayscale images.)
55. ATR Research, Kyoto, Japan
56. JISCT Stereo Evaluation - 44 image pairs. These data have been used in an evaluation of stereo analysis, as described in the April 1993 ARPA Image Understanding Workshop paper The JISCT Stereo Evaluation'' by R.C.Bolles, H.H.Baker, and M.J.Hannah, 263--274 (Formats: SSI)
57. MIT Vision Texture - Image archive (100+ images) (Formats: ppm)
58. MIT face images and more - hundreds of images (Formats: homebrew)
59. Machine Vision - Images from the textbook by Jain, Kasturi, Schunck (20+ images) (Formats: GIF TIFF)
60. Mammography Image Databases - 100 or more images of mammograms with ground truth. Additional images available by request, and links to several other mammography databases are provided. (Formats: homebrew)
61. ftp://ftp.cps.msu.edu/pub/prip - many images (Formats: unknown)
62. Middlebury Stereo Data Sets with Ground Truth - Six multi-frame stereo data sets of scenes containing planar regions. Each data set contains 9 color images and subpixel-accuracy ground-truth data. (Formats: ppm)
63. Middlebury Stereo Vision Research Page - Middlebury College
64. Modis Airborne simulator, Gallery and data set - High Altitude Imagery from around the world for environmental modeling in support of NASA EOS program (Formats: JPG and HDF)
65. NIST Fingerprint and handwriting - datasets - thousands of images (Formats: unknown)
66. NIST Fingerprint data - compressed multipart uuencoded tar file
67. NLM HyperDoc Visible Human Project - Color, CAT and MRI image samples - over 30 images (Formats: jpeg)
68. National Design Repository - Over 55,000 3D CAD and solid models of (mostly) mechanical/machined engineerign designs. (Formats: gif,vrml,wrl,stp,sat)
69. Geometric & Intelligent Computing Laboratory
70. OSU (MSU) 3D Object Model Database - several sets of 3D object models collected over several years to use in object recognition research (Formats: homebrew, vrml)
71. OSU (MSU/WSU) Range Image Database - Hundreds of real and synthetic images (Formats: gif, homebrew)
72. OSU/SAMPL Database: Range Images, 3D Models, Stills, Motion Sequences - Over 1000 range images, 3D object models, still images and motion sequences (Formats: gif, ppm, vrml, homebrew)
73. Signal Analysis and Machine Perception Laboratory
74. Otago Optical Flow Evaluation Sequences - Synthetic and real sequences with machine-readable ground truth optical flow fields, plus tools to generate ground truth for new sequences. (Formats: ppm,tif,homebrew)
75. Vision Research Group
76. ftp://ftp.limsi.fr/pub/quenot/opflow/testdata/piv/ - Real and synthetic image sequences used for testing a Particle Image Velocimetry application. These images may be used for the test of optical flow and image matching algorithms. (Formats: pgm (raw))
77. LIMSI-CNRS/CHM/IMM/vision
78. LIMSI-CNRS
79. Photometric 3D Surface Texture Database - This is the first 3D texture database which provides both full real surface rotations and registered photometric stereo data (30 textures, 1680 images). (Formats: TIFF)
80. SEQUENCES FOR OPTICAL FLOW ANALYSIS (SOFA) - 9 synthetic sequences designed for testing motion analysis applications, including full ground truth of motion and camera parameters. (Formats: gif)
81. Computer Vision Group
82. Sequences for Flow Based Reconstruction - synthetic sequence for testing structure from motion algorithms (Formats: pgm)
83. Stereo Images with Ground Truth Disparity and Occlusion - a small set of synthetic images of a hallway with varying amounts of noise added. Use these images to benchmark your stereo algorithm. (Formats: raw, viff (khoros), or tiff)
84. Stuttgart Range Image Database - A collection of synthetic range images taken from high-resolution polygonal models available on the web (Formats: homebrew)
85. Department Image Understanding
86. The AR Face Database - Contains over 4,000 color images corresponding to 126 people's faces (70 men and 56 women). Frontal views with variations in facial expressions, illumination, and occlusions. (Formats: RAW (RGB 24-bit))
87. Purdue Robot Vision Lab
88. The MIT-CSAIL Database of Objects and Scenes - Database for testing multiclass object detection and scene recognition algorithms. Over 72,000 images with 2873 annotated frames. More than 50 annotated object classes. (Formats: jpg)
89. The RVL SPEC-DB (SPECularity DataBase) - A collection of over 300 real images of 100 objects taken under three different illuminaiton conditions (Diffuse/Ambient/Directed). -- Use these images to test algorithms for detecting and compensating specular highlights in color images. (Formats: TIFF )
90. Robot Vision Laboratory
91. The Xm2vts database - The XM2VTSDB contains four digital recordings of 295 people taken over a period of four months. This database contains both image and video data of faces.
92. Centre for Vision, Speech and Signal Processing
93. Traffic Image Sequences and 'Marbled Block' Sequence - thousands of frames of digitized traffic image sequences as well as the 'Marbled Block' sequence (grayscale images) (Formats: GIF)
94. IAKS/KOGS
95. U Bern Face images - hundreds of images (Formats: Sun rasterfile)
96. U Michigan textures (Formats: compressed raw)
97. U Oulu wood and knots database - Includes classifications - 1000+ color images (Formats: ppm)
98. UCID - an Uncompressed Colour Image Database - a benchmark database for image retrieval with predefined ground truth. (Formats: tiff)
99. UMass Vision Image Archive - Large image database with aerial, space, stereo, medical images and more. (Formats: homebrew)
100. UNC's 3D image database - many images (Formats: GIF)
101. USF Range Image Data with Segmentation Ground Truth - 80 image sets (Formats: Sun rasterimage)
102. University of Oulu Physics-based Face Database - contains color images of faces under different illuminants and camera calibration conditions as well as skin spectral reflectance measurements of each person.
103. Machine Vision and Media Processing Unit
104. University of Oulu Texture Database - Database of 320 surface textures, each captured under three illuminants, six spatial resolutions and nine rotation angles. A set of test suites is also provided so that texture segmentation, classification, and retrieval algorithms can be tested in a standard manner. (Formats: bmp, ras, xv)
105. Machine Vision Group
106. Usenix face database - Thousands of face images from many different sites (circa 994)
107. View Sphere Database - Images of 8 objects seen from many different view points. The view sphere is sampled using a geodesic with 172 images/sphere. Two sets for training and testing are available. (Formats: ppm)
108. PRIMA, GRAVIR
109. Vision-list Imagery Archive - Many images, many formats
110. Wiry Object Recognition Database - Thousands of images of a cart, ladder, stool, bicycle, chairs, and cluttered scenes with ground truth labelings of edges and regions. (Formats: jpg)
111. 3D Vision Group
112. Yale Face Database - 165 images (15 individuals) with different lighting, expression, and occlusion configurations.
113. Yale Face Database B - 5760 single light source images of 10 subjects each seen under 576 viewing conditions (9 poses x 64 illumination conditions). (Formats: PGM)
114. Center for Computational Vision and Control
115. DeepMind QA Corpus - Textual QA corpus from CNN and DailyMail. More than 300K documents in total. Paper for reference.
116. YouTube-8M Dataset - YouTube-8M is a large-scale labeled video dataset that consists of 8 million YouTube video IDs and associated labels from a diverse vocabulary of 4800 visual entities.
117. Open Images dataset - Open Images is a dataset of ~9 million URLs to images that have been annotated with labels spanning over 6000 categories.
118. Visual Object Classes Challenge 2012 (VOC2012) - VOC2012 dataset containing 12k images with 20 annotated classes for object detection and segmentation.
119. Fashion-MNIST - MNIST like fashion product dataset consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes.
120. Large-scale Fashion (DeepFashion) Database - Contains over 800,000 diverse fashion images. Each image in this dataset is labeled with 50 categories, 1,000 descriptive attributes, bounding box and clothing landmarks
121. FakeNewsCorpus - Contains about 10 million news articles classified using opensources.co types

共计11个顶级会议，比如CVPR、IJCAI、ICML和NIPS等。

共计53个深度学习相关框架，比如TensorFlow、PyTorch、Keras、MXNet、Caffe等。

共计4个深度学习常用工具，如Jupyter Notebook和TensorBoard。

1. Netron - Visualizer for deep learning and machine learning models
2. Jupyter Notebook - Web-based notebook environment for interactive computing
3. TensorBoard - TensorFlow's Visualization Toolkit
4. Visual Studio Tools for AI - Develop, debug and deploy deep learning and AI solutions

共计33个深度学习相关资源，如速查表和优质开源项目等。

1. Google Plus - Deep Learning Community
2. Caffe Webinar
3. 100 Best Github Resources in Github for DL
4. Word2Vec
5. Caffe DockerFile
6. TorontoDeepLEarning convnet
7. gfx.js
8. Torch7 Cheat sheet
9. Misc from MIT's 'Advanced Natural Language Processing' course
10. Misc from MIT's 'Machine Learning' course
11. Misc from MIT's 'Networks for Learning: Regression and Classification' course
12. Misc from MIT's 'Neural Coding and Perception of Sound' course
13. Implementing a Distributed Deep Learning Network over Spark
14. A chess AI that learns to play chess using deep learning.
15. Reproducing the results of "Playing Atari with Deep Reinforcement Learning" by DeepMind
16. Wiki2Vec. Getting Word2vec vectors for entities and word from Wikipedia Dumps
17. The original code from the DeepMind article + tweaks
18. Google deepdream - Neural Network art
19. An efficient, batched LSTM.
20. A recurrent neural network designed to generate classical music.
21. Memory Networks Implementations - Facebook
22. Face recognition with Google's FaceNet deep neural network.
23. Basic digit recognition neural network
24. Emotion Recognition API Demo - Microsoft
25. Proof of concept for loading Caffe models in TensorFlow
26. YOLO: Real-Time Object Detection
27. AlphaGo - A replication of DeepMind's 2016 Nature publication, "Mastering the game of Go with deep neural networks and tree search"
28. Machine Learning for Software Engineers
29. Machine Learning is Fun!
30. Siraj Raval's Deep Learning tutorials
31. Dockerface - Easy to install and use deep learning Faster R-CNN face detection for images and video in a docker container.
32. Awesome Deep Learning Music - Curated list of articles related to deep learning scientific research applied to music
33. Awesome Graph Embedding - Curated list of articles related to deep learning scientific research on graph structured data at the graph level.
34. Awesome Network Embedding - Curated list of articles related to deep learning scientific research on graph structured data at the node level.

作者：ChristosChristofidis
来源：https://github.com/ChristosChristofidis/awesome-deep-learning

推荐阅读：
在线深度学习：在数据流中实时学习深度神经网络
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