Artificial Intelligence & Computer Vision & ML and DL
Ref:face_recognition
Ref:seetaface
Ref:百度AI开放平台
Ref:Face++开放平台
Ref:AForge.NET 入门
Ref:调用 AForge.NET Framework 启动摄像头
Ref:.NET开源工程推荐（Accord，AForge，Emgu CV）
Ref:http://www.aforgenet.com/framework/
Ref:http://www.aforgenet.com/framework/features/motion_detection_2.0.html
Ref:https://www.codeguru.com/columns/dotnet/computer-vision-using-aforge.net.html
Ref:http://www.arcsoft.com.cn/ai/arcface.html
Ref:http://www.emgu.com/wiki/index.php/Main_Page
Ref:http://www.emgu.com/wiki/index.php/Tutorial
Ref:Mac下dlib安装
Ref:Python3.6+dlib19.4在Mac下环境搭建
Ref:http://www.learnopencv.com/facial-landmark-detection
Ref:http://www.th7.cn/Program/Python/201511/706515.shtml
Ref:应用一个基于Python的开源人脸识别库，face_recognition
Ref:http://www.intorobotics.com/how-to-detect-and-track-object-with-opencv/
Ref:http://www.shervinemami.info/faceRecognition.html
Ref:https://www.pyimagesearch.com/2015/11/09/pedestrian-detection-opencv/
Ref:http://introlab.github.io/find-object/
Ref:https://github.com/TadasBaltrusaitis/OpenFace
Ref:https://github.com/TadasBaltrusaitis/CLM-framework
Ref:行人检测(Pedestrian Detection)资源
Ref:YOLO: Real-Time Object Detection
Ref:目标检测方法系列——R-CNN, SPP, Fast R-CNN, Faster R-CNN, YOLO, SSD
Ref:SeetaFace编译案例（windows&Android）
Ref:机器视觉开源代码集合
Start CPU only container
$ docker run -it -p 8888:8888 tensorflow/tensorflowGo to your browser on http://localhost:8888/
Start GPU (CUDA) container
Install nvidia-docker and run
$ nvidia-docker run -it -p 8888:8888 tensorflow/tensorflow:latest-gpuGo to your browser on http://localhost:8888/
Other versions (like release candidates, nightlies and more)
See the list of tags. Devel docker images include all the necessary dependencies to build from source whereas the other binaries simply have TensorFlow installed.
For more details details see
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/docker/README.md
随时更新———个人喜欢的关于模式识别、机器学习、推荐系统、图像特征、深度学习、数值计算、目标跟踪等方面个人主页及博客
http://blog.csdn.net/zhangping1987/article/details/29554621
目标检测、识别、分类、特征点的提取
David Lowe：Sift算法的发明者，天才。
Rob Hess：sift的源码OpenSift的作者，个人主页上有openSift的下载链接，Opencv中sift的实现，也是参考这个。
Koen van de Sande：作者给出了sift,densesift,colorsift等等常用的特征点程序，输出格式见个人主页说明，当然这个特征点的算法，在Opencv中都有实现。
Ivan Laptev：作者给出了物体检测等方面丰富C\C++源码，及部分训练好的检测器（包括汽车，行人，摩托车，马，猫脸的检测器）。
Navneet Dalal：HOG算子的作者，个人主页上有他本人的博士论文，写的异常精彩，还有HOG源码链接，当然强大的Opencv已经复现了一遍。
Anna Bosch:PHOG算法的作者及源码。
Carl Vondrick:作者主页上呈现了两个非常好的项目Video Annotation Tool（视频标注）和iHOG，iHOG很有意思的解释了，为什么HOG算法会误判的原因。哇！哇！精彩！
Antonio Torralba：场景识别GIST算子（Matlab）的作者，当然个人主页张还有sift folow等等源码，偷着乐吧，Gist的C代码。
Svetlana Lazebnik：空间金字塔匹配的作者，个人主页上有物体检测和识别的丰富源码。
Kristen Grauman：2011年的marr prize的得主，美女，源码libpmk的作者，个人主页还有其他物体检测和识别的文档和源码。
Pablo F. Alcantarilla:kaze和akaze特征点的作者，据说比sift要好，作者的个人主页上给出了这两种特征点的C++代码，高兴啊！
Pedro Felzenszwalb:近几年的物体识别竞赛，大都是根据他的源码的框架，Discriminatively trained deformable part models，直到2012年，该算法的版本是5，作者个人主页上有链接。
Opencv中，有该算法的复现，但是，没有训练的部分，只有检测的部分，latentsvmdetector。
在\opencv\sources\samples\cpp文件夹中，有一个latentsvm_multidetect.cpp文件，搭好环境，运行，然后，准备好图片（http://pascallin.ecs.soton.ac.uk/challenges/VOC/)和常见的20种分类器：
就可以做物体检测了。
沙发检测 自行车检测
猫检测 汽车检测
其他物体的检测，就不一一列举了。
Deva Ramanan:Histograms of Sparse Codes（HSC）算法的第二作者，作者的个人主页上有除了物体识别检测，还有几个跟踪算法的源码。
Xiaofeng Ren:Histograms of Sparse Codes（HSC）算法的第一作者，作者的个人主页有丰富的源码。
Ce Liu:Siftflow算法的作者，个人主页上具有其他算法的源码。
Derek Hoiem：（非常喜欢）个人主页有物体识别，检测的源码，而且有Logistic Regression of Adaboost源码，而且个人主页上有很多他的学生的个人主页链接。
Sergey Karayev：作者的个人主页上有基于颜色的图像检索，目标识别的研究成果。
Aditya Khosla：作者研究兴趣是人的行为检测，目标识别，等。
Ming-Ming Cheng:(mmcheng.net)
关注论文《BING: Binarized Normed Gradients for Objectness Estimation at 300fps》
Boris Babenko:还没开始看
Juergen Gall:hough forest的作者
Kaiming He：darkchannel的作者
Timo Ojala:LBP特征的作者
Cewu Lu:CVPR2014,晴天阴天的识别
————————————————————————————————————————————
还有一些没仔细看：很多源码
————————————————————————————————————————————
图像分割：
———————————————————————————————————————————————
图像检索、特征点匹配：
Yossi Rubner：（这个个人主页链接可能打不开，百度这个网址http://ai.stanford.edu/~rubner/根据提示打开就可以了）图像检索EMD距离的原作者，作者给出了C源码，Opencv中给出了复现，具体可以参看这篇文章。
Ofir Pele：EMD距离的改进，作者个人主页上给出了源码（C++\Matlab）。
Haibin Ling：EMD_L1算法的作者，而且作者给我C++代码
Qin Lv:美女教师，对EMD的应用讲解的很好
颜色信息：
A Data Set for Fuzzuy Color Naming
Rahat Khan:《Discriminative Color Descriptor》的作者
Robert Benavente:color naming TSEmodel
图像其他算法
Jiaya Jia：香港大学，发明的图像去模糊算法，处于世界领先水平，个人主页上有丰富的源码，超级喜欢。
Mohamed Aly:这个个人主页是无意中发现的，他研究了公路上各种直线（斑马线等）等的检测，并给出了源码。
__________________________________________________________________________________________________________________________________
人工智能博客：
Utkarsh:这个博客里写了好多关于OpenCV的项目，是一个非常好的学习资源。
Sebastian Montabone:作者写了一些很好的资料。
铅笔素描：
———————————————————————————————————————————————
机器学习及并行机器学习、模式识别：
dlib:人脸识别
Rakesh Agrawal：关联规则算法的原作者
Ramakrishnan Srikant :关联规则算法的原作者
Andrew Ng：谷歌大脑之父，是斯坦福大学科学系和电子工程系副教授，人工智能实验室主任。吴恩达是人工智能和机器学习领域国际上最权威的学者之一。吴恩达也是在线教育平台Coursera的联合创始人（withDaphne Koller）。
他的机器学习公开课：网易机器学习公开课。听一位大师，讲数学，原来是如此生动！并配有机器学习讲义。看完，之后，会对机器学习算法的认识有一个质的飞越。
Edward Chang:我是在吴军老师的《数学之美》中看到张智威老师，解决了并行SVD算法，但是，现在还没有任何关于这方面的资料。张智威老师的个人主页上，给出了关于并行支持向量机的算法，有一篇文章的符号，有一点混乱，我在这里给出了重新的计算和梳理。
Andrea Vedaldi：vlfeat源码的管理者之一，它近期写的关于支持向量机的文章很是喜欢，作者个人主页提供非常丰富的Matlab和C源码。
Ashesh Jain：作者的研究兴趣是机器学习和凸优化。作者的个人主页上有支持向量机的多核学习(Multiple Kernel Learning)源码。
Lin Chih-Jen：公认的最好的支持向量机开源libsvm，可以很好做Mercer Kernel做扩展，我添加常用11个Mercer核，并加在了libsvm中。推荐系统源码libmf。非负矩阵分解源码NMF。
Journal of Machine Learning Research：在线提供了非常多的机器学习论文及源码，个人非常喜欢。
Martin Ester:基于密度的聚类算法DBSCAN的作者。作者主页上有他的所有著作。
Department of Computer Science Database Systems Group:聚类
Jiawei Han：关联规则算法之FP_tree的作者
Geoffrey E. Hinton:Deep Learning(无需多说)
Josef Sivic:PLSA的源码
Thomas Hofmann:PLSA的原作者
David M. Blei:LDA的作者，作者提供源码
gustau camps-valls:libsvm有关，还没看
Andrew I. Schein:LogisticPCA的作者
Boost家族：
Yoav Freund:AdaBoost算法的作者主页
Jerome H. Friedman：LogitBoost和 Gradient Boost回归算法的作者主页，并有这些算法的R语言源码。
《Stochastic Gradient Boosting》
《Greedy Function Approximation: A Gradient Boosting Machine》
《Additive Logistic Regression：a Statistical View of Boosting 》必须打印，认真研究的论文
边缘检测、图像滤波、阈值处理
-------------------------------------------------------------------------------------------------------------------
————————————————————————————————————————————————————————————————————————————
计算机视觉团队：这三个团队主页上，提供了图像和视频算法的大量研究成果
-----------------------
___________________________________________________________________________________________________________________________________
推荐系统：
Yehuda Koren：Netflix prize 推荐系统算法冠军成员， SVD++
__________________________________________________________________________________________________________________________________
数值计算：
LinPack：线性最小二乘，矩阵的奇异值分解等
MinPack：非线性最小二乘
跟踪算法：
http://research.milanton.de/index.html
SHENGFENG He：LSH
其他常用的图像处理库：
Leptonica
Tesseract
运动物体检测
自然语言处理：
谭松波:中文文本分类语料库
数据的可视化：
神经网络
基于颜色检索的参考网站：
https://www.etsy.com/color.php
http://labs.tineye.com/multicolr/
------------------------------------------------------
概率霍夫检测
http://www.sunshine2k.de/coding/java/Houghtransformation/HoughTransform.html
http://www.keymolen.com/2013/05/hough-transformation-c-implementation.html
深度学习:
关于OpenCV的特征点的一些好的博客：
YOLOv2物体检测
keras-yolo3（A Keras implementation of YOLOv3 (Tensorflow backend) inspired by allanzelener/YAD2K.）
Keras
Keras中文文档 | 预训练权重的Keras模型 | https://github.com/ufoym/deepo | Deep Learning with Docker
1、keras系列︱Sequential与Model模型、keras基本结构功能（一）
2、keras系列︱Application中五款已训练模型、VGG16框架（Sequential式、Model式）解读（二）
3、keras系列︱图像多分类训练与利用bottleneck features进行微调（三）
4、keras系列︱人脸表情分类与识别：opencv人脸检测+Keras情绪分类（四）
5、keras系列︱迁移学习：利用InceptionV3进行fine-tuning及预测、完整案例（五）
其他
用 Scikit-Learn 和 Pandas 学习线性回归
Which machine learning algorithm should I use?
有趣的机器学习概念纵览：从多元拟合，神经网络到深度学习，给每个感兴趣的人
TensorFlow和深度学习入门教程（TensorFlow and deep learning without a PhD）
An Introduction to Machine Learning Theory and Its Applications: A Visual Tutorial with Examples
DL4J与Torch、Theano、TensorFlow、Caffe、Paddle、MxNet、Keras 和 CNTK的比较
23 种深度学习库排行榜：TensorFlow、Keras、Caffe 占据前三！
超详细配置Caffe(gpu版本+ubuntu16.04)考虑各种问题
可能是近期最好玩的深度学习模型：CycleGAN的原理与实验详解
卷积神经网络CNN经典模型整理Lenet，Alexnet，Googlenet，VGG，Deep Residual Learning
秒懂！何凯明的深度残差网络PPT是这样的|ICML2016 tutorial
http://neuralnetworksanddeeplearning.com
https://github.com/Microsoft/MMdnn
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch and CoreML.
deeplearning.net
- a reading list,
- links to software,
- datasets,
- a list of deep learning research groups and labs,
- a list of announcements for deep learning related jobs (job listings),
- as well as tutorials and cool demos.
- announcements and news about deep learning
深度学习开源项目整理
转自https://silencezjl.coding.me/2017/05/01/%E5%81%B7%E4%B8%80%E6%B3%A2%E8%B5%84%E6%BA%90/
Deeplearining Datasets
http://deeplearning.net/datasets/
深度学习视觉领域常用数据集汇总
数据集大全：25个深度学习的开放数据集
https://yq.aliyun.com/articles/576274
深度学习常用的Data Set数据集和CNN Model总结
https://blog.csdn.net/qq_17448289/article/details/52850223
基于TensorFlow的框架
https://github.com/fchollet/keras
https://github.com/tflearn/tflearn
https://github.com/beniz/deepdetect
https://github.com/tensorflow/fold
https://github.com/leriomaggio/deep-learning-keras-tensorflow
精选入门教程
https://github.com/tensorflow/models
https://github.com/aymericdamien/TensorFlow-Examples
https://github.com/donnemartin/data-science-ipython-notebooks
https://github.com/jtoy/awesome-tensorflow
https://github.com/jikexueyuanwiki/tensorflow-zh
https://github.com/nlintz/TensorFlow-Tutorials
https://github.com/pkmital/tensorflow_tutorials
https://github.com/deepmind/learning-to-learn
https://github.com/BinRoot/TensorFlow-Book
https://github.com/jostmey/NakedTensor
https://github.com/alrojo/tensorflow-tutorial
https://github.com/CreatCodeBuild/TensorFlow-and-DeepLearning-Tutorial
https://github.com/sjchoi86/Tensorflow-101
https://github.com/chiphuyen/tf-stanford-tutorials
https://github.com/google/prettytensor
https://github.com/ahangchen/GDLnotes
https://github.com/Hvass-Labs/TensorFlow-Tutorials
https://github.com/NickShahML/tensorflow_with_latest_papers
https://github.com/nfmcclure/tensorflow_cookbook
https://github.com/ppwwyyxx/tensorpack
https://github.com/rasbt/deep-learning-book
https://github.com/pkmital/CADL
https://github.com/tensorflow/skflow
无人驾驶
https://github.com/kevinhughes27/TensorKart
https://github.com/SullyChen/Autopilot-TensorFlow
深度强化学习
https://github.com/dennybritz/reinforcement-learning
https://github.com/zsdonghao/tensorlayer
https://github.com/matthiasplappert/keras-rl
https://github.com/nivwusquorum/tensorflow-deepq
https://github.com/devsisters/DQN-tensorflow
https://github.com/coreylynch/async-rl
https://github.com/carpedm20/deep-rl-tensorflow
https://github.com/yandexdataschool/Practical_RL
自然语言处理
文本分类
https://github.com/dennybritz/cnn-text-classification-tf
序列建模
https://github.com/google/seq2seq
中文分词
基于文本的图像合成
https://github.com/paarthneekhara/text-to-image
RNN语言建模
https://github.com/sherjilozair/char-rnn-tensorflow
https://github.com/silicon-valley-data-science/RNN-Tutorial
神经图灵机
https://github.com/carpedm20/NTM-tensorflow
小黄鸡
https://github.com/wong2/xiaohuangji
语音领域
语音合成
https://github.com/ibab/tensorflow-wavenet
https://github.com/tomlepaine/fast-wavenet
语音识别
https://github.com/buriburisuri/speech-to-text-wavenet
https://github.com/pannous/tensorflow-speech-recognition
计算机视觉
风格转换
https://github.com/anishathalye/neural-style
https://github.com/cysmith/neural-style-tf
运用GAN图像生成
https://github.com/carpedm20/DCGAN-tensorflow
图像到图像的翻译
https://github.com/affinelayer/pix2pix-tensorflow
图像超分辨
https://github.com/Tetrachrome/subpixel
人脸识别
https://github.com/davidsandberg/facenet
目标检测
https://github.com/TensorBox/TensorBox
运动识别
https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition
图像复原
https://github.com/bamos/dcgan-completion.tensorflow
生成模型
https://github.com/wiseodd/generative-models
TensorFlow实时debug工具
https://github.com/ericjang/tdb
TensorFlow在树莓派上的应用
https://github.com/samjabrahams/tensorflow-on-raspberry-pi
TensorFlow基于R的应用
https://github.com/rstudio/tensorflow
实时Spark与TensorFlow的输入pipeline
https://github.com/fluxcapacitor/pipeline
https://github.com/yahoo/TensorFlowOnSpark
caffe与TensorFlow结合
https://github.com/ethereon/caffe-tensorflow
概率建模
https://github.com/blei-lab/edward
大牛github网址收藏
关于文本分类：https://github.com/ChengjinLi/machine_learning
关于聊天机器人：https://github.com/MarkWuNLP/MultiTurnResponseSelection
博客关于物体识别
https://pjreddie.com/darknet/yolo/
基于知识图谱的厨房领域问答系统构建
PDF Ref
Computer Vision
- Dropbox_Imagenet-Classification-with-Deep-Convolutional-Neural-Networks
- Dropbox_Visualizing-and-Understanding-Convolutional-Networks
- Dropbox_Long-term-Recurrent-Convolutional-Networks-for-Visual-Recognition-and-Description
- Dropbox_One-weird-trick-for-parallelizing-convolutional-neural-networks
- Dropbox_Going-deeper-with-convolutions
- Dropbox_Deep-Residual-Learning-for-Image-Recognition
- Dropbox_Batch-Normalization-Accelerating-Deep-Network-Training-by-Reducing-Internal-Covariate-Shift
- Dropbox_Semi-supervised-Convolutional-Neural-Networks-for-Text-Categorization-via-Region-Embedding
- Dropbox_Show-and-Tell-A-Neural-Image-Caption-Generator
- Dropbox_Rethinking-the-Inception-Architecture-for-Computer-Vision-Inception-v3
- Dropbox_Very-Deep-Convolutional-Networks-For-Large-Scale-Image-Recognition
- Dropbox_Identity-Mappings-in-Deep-Residual-Networks
- Dropbox_Wide-Residual-Nets
- Dropbox_Dynamic-Routing-between-capsules
- Dropbox_Matrix-Capsules-with-EM-rounting
- Dropbox_Identity-Mappings-in-Deep-Residual-Networks
Natural Language Processing
- Dropbox_Deep-Almond-A-Deep-Learning-based-Virtual
- Dropbox_A_neural_conversational_model
- Dropbox_Memory_Networks
- Dropbox_Supervised-Sequence-Labelling-with-Recurrents
- Dropbox_The-Unreasonable-Effectiveness-of-Recurrent-Neural-Networks
- Dropbox_Deep-Learning-for-Textual-Big-Data-Analysis
- Dropbox_Sequence-to-Sequence-Learning
- Dropbox_On-the-Properties-of-Neural-Machine-Translation-Encoder–Decoder-seq2seq
- Dropbox_Learning-Phrase-Representations-using-RNN-Encoder–Decoder-seq2seq
- Dropbox_On-Using-Very-Large-Target-Vocabulary-for-Neural-Machine-Translation
- Dropbox_Addressing-the-Rare-Word-Problem-in-Neural-Machine-Translation
- Dropbox_Achieving-Open-Vocabulary-Neural-Machine-Translation
- Dropbox_Google’s-Neural-Machine-Translation-System-Bridging-the-Gap-between-Human-and-Machine-Translation
- Dropbox_Neural-Machine-Translation-by-Jointly-Learning-to-Align-and-Translate-seq2seq-with-attention
- Dropbox_Incorporating-Structural-Alignment-Biases-into-an-Attentional-Neural-Translation-Model
- Dropbox_Neural-Machine-Translation-of-Rare-Words-with-Subword-Units
- Dropbox_Beam-Search-Strategies-for-Neural-Machine-Translation
- Dropbox_Neural-Machine-Translation-and-Sequence-to-sequence-Models-a-Tutorial
- Dropbox_Generating-News-Headlines-with-Recurrent-Neural
- Dropbox_Abstractive-Text-Summarization-using-Sequence-to-sequence-RNNs-and-Beyond
- Dropbox_SocherPenningtonHuangNgManning_EMNLP2011
- Dropbox_Recursive-Deep-Models-for-Semantic-Compositionality
- Dropbox_Recurrent-Convolutional-Neural-Networks-for-Text-Classification
- Dropbox_Visualizing-and-Understanding-Recurrent-Networks
- Dropbox_Learning-text-representation-using-recurrent-convolutional-neural-network-with-highway-layers
- Dropbox_Paper_57-Sentiment_Analysis_using_Deep_Learning
Books
- Dropbox_Sutton-bookdraft2016aug
- Dropbox_TensorFlow-For-Machine-Intellig-Sam-Abrahams
- Dropbox_Ian_Goodfellow_Yoshua_Bengio_Aaron_Courville_DBookZZ.org-Deep-Learning
- Dropbox_Chollet
- Dropbox_TensorFlow-Machine-Learning-Cookbook
Deep Reinforcement Learning
- Dropbox_Reinforcement-Learning-Sutton-Barto
- Dropbox_Wiley-Series-in-Probability-and-Statistics-Martin-L.-Puterman-Markov-decision-processes.-Discrete-stochastic-dynamic-programming-MVspa-Wiley-Interscience-2005
- Dropbox_Monte-Carlo-Methods-Kalos-Whitlock
- Dropbox_Introduction-to-Stochastic-Dynamic-Programming-Ross
- Dropbox_Playing-Atari-with-Deep-Reinforcement-Learning
- Dropbox_Replicating-DeepMind
- Dropbox_Mastering_the_game_of_Go_with_deep_neural_networks_and_tree_search
- Dropbox_Asynchronous-Methods-for-Deep-Reinforcement-Learning
- Dropbox_Mastering-Chess-and-Shogi-by-Self-Play-with-a-General-Reinforcement-Learning-Algorithm
- Dropbox_Mastering-the-Game-of-Go-without-Human-Knowledge
Other
- Dropbox_Big-Data-and-Deep-Learning
- Dropbox_Data-intensive-applications-challenges-techniques-and-technologies-A-survey-on-Big-Data
- Dropbox_Deep-Learning-for-Visual-Big-Data-Analysis
- Dropbox_Big-Data-and-Deep-Learning
100 Best GitHub: Deep Learning
Notes:
This 100 item list represents a search of github for “deep-learning”, Nov 2017.
Resources:
- aforgenet.com .. (microsoft.com/net + accord-framework.net = windows)
- caffe.berkeleyvision.org .. speed makes caffe perfect for industry use
- developer.nvidia.com/cudnn .. gpu-accelerated library of primitives for deep neural networks
- github.com/maddin79/darch .. create deep architectures in the r programming language
- deeplearning4j.org .. commercial-grade deep-learning library written in java
- keras.io .. theano-based deep learning library
- deeplearning.net/software/theano .. gpu based model training and automatic code optimization in python
- h2o.ai .. an open source parallel processing engine for machine learning
Wikipedia:
References:
See also:
100 Best Deep Belief Network Videos | 100 Best Deep Learning Videos | 100 Best DeepMind Videos | 100 Best Jupyter Notebook Videos | 100 Best MATLAB Videos | Deep Belief Network & Dialog Systems | Deep Learning & Dialog Systems 2016 | Deep Reasoning Systems | DeepDive | DNLP (Deep Natural Language Processing) | MATLAB & Dialog Systems 2016 | Skipgram & Deep Learning 2016 | Word2vec Neural Network
- tensorflow/tensorflow computation using data flow graphs for scalable machine learning
- opencv/opencv open source computer vision library
- bvlc/caffe caffe: a fast open framework for deep learning.
- fchollet/keras deep learning library for python. runs on tensorflow, theano, or cntk.
- aymericdamien/tensorflow-examples tensorflow tutorial and examples for beginners with latest apis
- apache/incubator-mxnet lightweight, portable, flexible distributed/mobile deep learning with dynamic, mutation-aware dataflow dep scheduler;…
- ty4z2008/qix machine learning?deep learning?postgresql?distributed system?node.js?golang
- exacity/deeplearningbook-chinese deep learning book chinese translation
- deeplearning4j/deeplearning4j deep learning for java, scala & clojure on hadoop & spark with gpus – from skymind
- microsoft/cntk microsoft cognitive toolkit (cntk), an open source deep-learning toolkit
- zuzoovn/machine-learning-for-software-engineers a complete daily plan for studying to become a machine learning engineer.
- songrotek/deep-learning-papers-reading-roadmap deep learning papers reading roadmap for anyone who are eager to learn this amazing tech!
- donnemartin/data-science-ipython-notebooks data science python notebooks: deep learning (tensorflow, theano, caffe, keras), scikit-learn, kaggle, big data (spar…
- mnielsen/neural-networks-and-deep-learning code samples for my book “neural networks and deep learning”
- terryum/awesome-deep-learning-papers the most cited deep learning papers
- christoschristofidis/awesome-deep-learning a curated list of awesome deep learning tutorials, projects and communities.
- pytorch/pytorch tensors and dynamic neural networks in python with strong gpu acceleration
- oxford-cs-deepnlp-2017/lectures oxford deep nlp 2017 course
- rasmusbergpalm/deeplearntoolbox matlab/octave toolbox for deep learning. includes deep belief nets, stacked autoencoders, convolutional neural nets, …
- ageron/handson-ml a series of jupyter notebooks that walk you through the fundamentals of machine learning and deep learning in python …
- udacity/deep-learning repo for the deep learning nanodegree foundations program.
- daviddao/deeplearningbook mit deep learning book in pdf format
- cmusatyalab/openface face recognition with deep neural networks.
- lisa-lab/deeplearningtutorials deep learning tutorial notes and code. see the wiki for more info.
- wepe/machinelearning basic machine learning and deep learning
- karpathy/convnetjs deep learning in javascript. train convolutional neural networks (or ordinary ones) in your browser.
- chiphuyen/stanford-tensorflow-tutorials this repository contains code examples for the course cs 20si: tensorflow for deep learning research.
- kjw0612/awesome-deep-vision a curated list of deep learning resources for computer vision
- ujjwalkarn/machine-learning-tutorials machine learning and deep learning tutorials, articles and other resources
- tflearn/tflearn deep learning library featuring a higher-level api for tensorflow.
- bulutyazilim/awesome-datascience ? an awesome data science repository to learn and apply for real world problems.
- paddlepaddle/paddle parallel distributed deep learning
- kailashahirwar/cheatsheets-ai essential cheat sheets for deep learning and machine learning researchers
- amaas/stanford_dl_ex programming exercises for the stanford unsupervised feature learning and deep learning tutorial
- caffe2/caffe2 caffe2 is a lightweight, modular, and scalable deep learning framework.
- hangtwenty/dive-into-machine-learning dive into machine learning with python jupyter notebook and scikit-learn!
- yusugomori/deeplearning deep learning (python, c, c++, java, scala, go)
- lazyprogrammer/machine_learning_examples a collection of machine learning examples and tutorials.
- hvass-labs/tensorflow-tutorials tensorflow tutorials with youtube videos
- davisking/dlib a toolkit for making real world machine learning and data analysis applications in c++
- yenchenlin/deeplearningflappybird flappy bird hack using deep reinforcement learning (deep q-learning).
- h2oai/h2o-3 open source fast scalable machine learning api for smarter applications (deep learning, gradient boosting, random for…
- davidsandberg/facenet face recognition using tensorflow
- explosion/spacy ? industrial-strength natural language processing (nlp) with python and cython
- nvidia/digits deep learning gpu training system
- cmu-perceptual-computing-lab/openpose openpose: real-time multi-person keypoint detection library for body, face, and hands estimation
- tiny-dnn/tiny-dnn header only, dependency-free deep learning framework in c++14
- lengstrom/fast-style-transfer tensorflow cnn for fast style transfer!
- rushter/mlalgorithms minimal and clean examples of machine learning algorithms
- eriklindernoren/ml-from-scratch python implementations of machine learning models and algorithms from scratch. aims to cover everything from data min…
- hunkim/deeplearningzerotoall tensorflow basic tutorial labs
- chainer/chainer a flexible framework of neural networks for deep learning
- hironsan/bosssensor hide screen when boss is approaching.
- yunjey/pytorch-tutorial pytorch tutorial for deep learning researchers
- nervanasystems/neon intel® nervana™ reference deep learning framework committed to best performance on all hardware
- tzutalin/labelimg ? labelimg is a graphical image annotation tool and label object bounding boxes in images
- alexjc/neural-enhance super resolution for images using deep learning.
- fchollet/deep-learning-models keras code and weights files for popular deep learning models.
- amzn/amazon-dsstne deep scalable sparse tensor network engine (dsstne) is an amazon developed library for building deep learning (dl) ma…
- zsdonghao/tensorlayer tensorlayer: deep learning and reinforcement learning library for researcher and engineer.
- mlpack/mlpack mlpack: a scalable c++ machine learning library —
- owainlewis/awesome-artificial-intelligence a curated list of artificial intelligence (ai) courses, books, video lectures and papers
- dennybritz/deeplearning-papernotes summaries and notes on deep learning research papers
- leriomaggio/deep-learning-keras-tensorflow introduction to deep neural networks with keras and tensorflow
- conchylicultor/deepqa my tensorflow implementation of “a neural conversational model”, a deep learning based chatbot
- junyanz/cyclegan software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
- aymericdamien/topdeeplearning a list of popular github projects related to deep learning
- tencent/ncnn ncnn is a high-performance neural network inference framework optimized for the mobile platform
- phillipi/pix2pix image-to-image translation with conditional adversarial nets
- koth/kcws deep learning chinese word segment
- vahidk/effectivetensorflow tensorflow tutorials and best practices.
- kuleshov/cs228-material teaching materials for the probabilistic graphical models and deep learning classes at stanford
- martin-gorner/tensorflow-mnist-tutorial sample code for “tensorflow and deep learning, without a phd” presentation and code lab.
- pkmital/cadl course materials/homework materials for the free mooc course on “creative applications of deep learning w/ tensorflow…
- oreilly-japan/deep-learning-from-scratch deep learning
- thtrieu/darkflow translate darknet to tensorflow. load trained weights, retrain/fine-tune using tensorflow, export constant graph def …
- blei-lab/edward a library for probabilistic modeling, inference, and criticism. deep generative models, variational inference. runs o…
- baidu/mobile-deep-learning this research aims at simply deploying cnn(convolutional neural network) on mobile devices, with low complexity and h…
- tonybeltramelli/pix2code pix2code: generating code from a graphical user interface screenshot
- david-gpu/srez image super-resolution through deep learning
- zhec/realtime_multi-person_pose_estimation code repo for realtime multi-person pose estimation in cvpr’17 (oral)
- vdumoulin/conv_arithmetic a technical report on convolution arithmetic in the context of deep learning
- swift-ai/swift-ai the swift machine learning library.
- floydhub/dl-docker an all-in-one docker image for deep learning. contains all the popular dl frameworks (tensorflow, theano, torch, caff…
- ppwwyyxx/tensorpack a neural net training interface on tensorflow
- tensorflow/skflow simplified interface for tensorflow (mimicking scikit learn) for deep learning
- creatcodebuild/tensorflow-and-deeplearning-tutorial tensorflow & deep learning tutorial
- tobegit3hub/tensorflow_template_application tensorflow template application for deep learning
- openai/requests-for-research a living collection of deep learning problems
- intel-analytics/bigdl bigdl: distributed deep learning library for apache spark
- wendykan/deeplearningmovies kaggle’s competition for using google’s word2vec package for sentiment analysis
- balancap/ssd-tensorflow single shot multibox detector in tensorflow
- junyanz/pytorch-cyclegan-and-pix2pix image-to-image translation in pytorch (e.g. horse2zebra, edges2cats, and more)
- paddlepaddle/book deep learning 101 with paddlepaddle
- liuzhuang13/densenet densely connected convolutional networks, in cvpr 2017 (best paper award).
- nitishsrivastava/deepnet implementation of some deep learning algorithms.
- exacity/simplified-deeplearning simplified implementations of deep learning related works
- spandan-madan/deeplearningproject an in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.
- riweichen/deepface face analysis mainly based on caffe. at this time, face analysis tasks like detection, alignment and recognition have…
- pair-code/deeplearnjs hardware-accelerated deep learning and linear algebra (numpy) library for the web.
