15大领域，50篇文章，热门的50个机器学习应用

转自：https://medium.mybridge.co/learn-to-build-a-machine-learning-application-from-top-articles-of-2017-cdd5638453fc
https://github.com/Mybridge/learn-machine-learning
https://blog.csdn.net/dqcfkyqdxym3f8rb0/article/details/79251305

根据《纽约时报》的说法，“在硅谷招募机器学习工程师、数据科学家的情形，越来越像NFL选拔职业运动员，没有苛刻的训练很难上场了。”毕竟，高达124472美元的平均年薪可不是谁想挣就能挣到的。

正如职业运动员每天都要训练一样，机器学习的日常练习也是工程师生涯得以大踏步前进的基本保障。仅2017年一年，机器学习领域总结此类实战经验的文章便已超过20000篇，该领域相关职位的热度自是可见一斑。

从中，我们筛选出50篇最好的经验和心得，囊括了机器学习在15大细分领域的各项典型应用：

1. 图像处理

2. 风格迁移

3. 图像分类

4. 面部识别

5. 视频稳像

6. 目标检测

7. 自动驾驶

8. 推荐系统

9. AI游戏

10. AI棋手

11. AI医疗

12. AI语音

13. AI音乐

14. 自然语言处理

15. 学习预测

当然，如果你只是一个刚要准备上手机器学习的新人，我们推荐你优先考虑以下两个高分实战课程：

A) AI游戏【推荐：5041；评分：4.7/5】

The Beginner’s Guide to Building an Artificial Intelligence in Unity

• 链接：https://www.udemy.com/artificial-intelligence-in-unity/

B) 计算机视觉【推荐：8161；评分：4.5/5】

Deep Learning and Computer Vision A-Z™: Learn OpenCV, SSD & GANs and create image recognition apps

• 链接：https://www.udemy.com/computer-vision-a-z/

而对具体的实战经验，接下来我们分领域一一来看：

图像处理

1、High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

• GitHub：https://github.com/NVIDIA/pix2pixHD

• 论文：https://arxiv.org/abs/1711.11585

• 博客：https://tcwang0509.github.io/pix2pixHD/

2、Using Deep Learning to Create Professional-Level Photographs

• GitHub：https://github.com/google/creatism

• 论文：https://arxiv.org/abs/1707.03491

• 博客：https://research.googleblog.com/2017/07/using-deep-learning-to-create.html

3、High Dynamic Range (HDR) Imaging using OpenCV (Python)

• 项目：https://www.learnopencv.com/high-dynamic-range-hdr-imaging-using-opencv-cpp-python/

• 课程主页：https://courses.learnopencv.com/p/opencv-for-beginners

风格迁移

4、Visual Attribute Transfer through Deep Image Analogy

• GitHub：https://github.com/msracver/Deep-Image-Analogy

• 论文：https://arxiv.org/abs/1705.01088

5、Deep Photo Style Transfer

• GitHub：https://github.com/luanfujun/deep-photo-styletransfer

• 论文：https://arxiv.org/abs/1703.07511

6、Deep Image Prior

• GitHub：https://github.com/DmitryUlyanov/deep-image-prior

• 论文：https://arxiv.org/abs/1711.10925

• 博客：https://dmitryulyanov.github.io/deep_image_prior

图像分类

7、Feature Visualization: How neural networks build up their understanding of images.

• 论文：https://distill.pub/2017/feature-visualization/

• 代码：https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/deepdream/deepdream.ipynb

• 博客：https://colah.github.io/

8、An absolute beginner’s guide to Image Classification with Neural Networks

• Github【4491收藏】：https://github.com/humphd/have-fun-with-machine-learning

• 中文版：https://github.com/humphd/have-fun-with-machine-learning/blob/master/README_zh-tw.md

9、Background removal with deep learning

• 模型：https://towardsdatascience.com/background-removal-with-deep-learning-c4f2104b3157

• 部署：https://medium.com/@burgalon/deploying-your-keras-model-35648f9dc5fb

面部识别

10、Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression

• GitHub：https://github.com/AaronJackson/vrn

• 论文：https://arxiv.org/abs/1703.07834

• 博客：http://aaronsplace.co.uk/papers/jackson2017recon/

• Demo：http://cvl-demos.cs.nott.ac.uk/vrn/

11、Eye blink detection with OpenCV, Python, and dlib

• 项目：https://www.pyimagesearch.com/2017/04/24/eye-blink-detection-opencv-python-dlib/

• 论文：http://vision.fe.uni-lj.si/cvww2016/proceedings/papers/05.pdf

12、DEAL WITH IT in Python with Face Detection

• GitHub：https://github.com/burningion/automatic-memes

• 博客：https://www.makeartwithpython.com/blog/deal-with-it-generator-face-recognition/

视频稳像

13、Fused Video Stabilization on the Pixel 2 and Pixel 2 XL

• 博客：https://research.googleblog.com/2017/11/fused-video-stabilization-on-pixel-2.html

• 测评：https://www.dxomark.com/google-pixel-2-reviewed-sets-new-record-smartphone-camera-quality/

目标检测

14、How HBO’s Silicon Valley built “Not Hotdog” with mobile TensorFlow and Keras

• 博客：https://medium.com/@timanglade/how-hbos-silicon-valley-built-not-hotdog-with-mobile-tensorflow-keras-react-native-ef03260747f3

• 项目：https://github.com/kmather73/NotHotdog-Classifier

15、Object detection: an overview in the age of Deep Learning

• GitHub：https://github.com/tryolabs/luminoth

• 论文：https://tryolabs.com/blog/2017/08/30/object-detection-an-overview-in-the-age-of-deep-learning/

16、How to train your own Object Detector with TensorFlow’s Object 

Detector API

• 博客：https://towardsdatascience.com/how-to-train-your-own-object-detector-with-tensorflows-object-detector-api-bec72ecfe1d9

• 数据集：https://github.com/datitran/raccoon_dataset

• 产品化：https://towardsdatascience.com/building-a-real-time-object-recognition-app-with-tensorflow-and-opencv-b7a2b4ebdc32

• 产品代码：https://github.com/datitran/object_detector_app

17、Real-time object detection with deep learning and OpenCV

• 实战：https://www.pyimagesearch.com/2017/09/18/real-time-object-detection-with-deep-learning-and-opencv/

• 入门：

①https://www.pyimagesearch.com/2017/09/11/object-detection-with-deep-learning-and-opencv/；②https://www.pyimagesearch.com/2016/01/04/unifying-picamera-and-cv2-videocapture-into-a-single-class-with-opencv/

③https://www.pyimagesearch.com/2017/08/21/deep-learning-with-opencv/

自动驾驶

18、Self-driving Grand Theft Auto V with Python : Intro [Part I]

• GitHub：https://github.com/sentdex/pygta5

• 视频：https://www.youtube.com/playlist?list=PLQVvvaa0QuDeETZEOy4VdocT7TOjfSA8a

• 博客：https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/

19、Recognizing Traffic Lights With Deep Learning: How I learned deep learning in 10 weeks and won $5,000

• GitHub：https://github.com/davidbrai/deep-learning-traffic-lights

• 博客：https://medium.freecodecamp.org/recognizing-traffic-lights-with-deep-learning-23dae23287cc

• 相关比赛：https://www.getnexar.com/challenge-1/

推荐系统

20、Spotify’s Discover Weekly: How machine learning finds your new music

• 实战：https://hackernoon.com/spotifys-discover-weekly-how-machine-learning-finds-your-new-music-19a41ab76efe

• 演讲：https://www.youtube.com/watch?v=A259Yo8hBRs

• 相关博客： ①http://benanne.github.io/2014/08/05/spotify-cnns.html ②https://notes.variogr.am/2012/12/11/how-music-recommendation-works-and-doesnt-work/

21、Artwork Personalization at Netflix

• 博客：https://medium.com/netflix-techblog/artwork-personalization-c589f074ad76

• 论文：https://arxiv.org/abs/1003.5956

• 原理介绍：http://highscalability.com/blog/2017/12/11/netflix-what-happens-when-you-press-play.html

AI游戏

22、MariFlow — Self-Driving Mario Kart w/Recurrent Neural Network

• 文档：https://docs.google.com/document/d/1p4ZOtziLmhf0jPbZTTaFxSKdYqE91dYcTNqTVdd6es4

• 视频：https://www.youtube.com/watch?v=Ipi40cb_RsI

23、OpenAI Baselines: DQN

• GitHub：https://github.com/openai/baselines

• 项目主页：https://blog.openai.com/openai-baselines-dqn/

24、Reinforcement Learning on Dota 2 [Part II]

• 博客：https://blog.openai.com/more-on-dota-2/

• 视频：https://openai.com/the-international/

25、Creating an AI DOOM bot

• 博客：https://www.codelitt.com/blog/doom-ai/

• 工具：http://vizdoom.cs.put.edu.pl/

26、Phase-Functioned Neural Networks for Character Control

• 博客：http://theorangeduck.com/page/phase-functioned-neural-networks-character-control

• 代码：http://theorangeduck.com/media/uploads/other_stuff/pfnn.zip

• 论文：http://theorangeduck.com/media/uploads/other_stuff/phasefunction.pdf

• 视频：http://theorangeduck.com/media/uploads/other_stuff/phasefunction.mov

27、The Game Imitation: Deep Supervised Convolutional Networks for Quick Video Game AI

• 论文：https://arxiv.org/abs/1702.05663

• 视频：https://www.youtube.com/playlist?list=PLegUCwsQzmnUpPwVv8ygMa19zNnDgJ6OC

28、Introducing: Unity Machine Learning Agents

• GitHub：https://github.com/Unity-Technologies/ml-agents

• 博客：https://blogs.unity3d.com/cn/2017/09/19/introducing-unity-machine-learning-agents/

• 文档：https://github.com/Unity-Technologies/ml-agents/tree/master/docs

AI棋手

29、Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

• 论文：https://arxiv.org/abs/1712.01815

• 演讲：http://ktiml.mff.cuni.cz/~bartak/ui_seminar/talks/2017ZS/KarelHa_AlphaZero.pdf 模型：https://deepmind.com/research/alphago/alphazero-resources/

• 相关实现： ①https://github.com/mokemokechicken/reversi-alpha-zero ②https://web.stanford.edu/~surag/posts/alphazero.html

30、AlphaGo Zero: Learning from scratch

• 博客：https://deepmind.com/blog/alphago-zero-learning-scratch/

• 论文：https://deepmind.com/documents/119/agz_unformatted_nature.pdf

• 棋谱：http://www.alphago-games.com/

31、How Does DeepMind’s AlphaGo Zero Work?

• GitHub：https://github.com/llSourcell/alphago_demo

• 视频：https://www.youtube.com/watch?v=vC66XFoN4DE

32、A step-by-step guide to building a simple chess AI

• GitHub：https://github.com/lhartikk/simple-chess-ai

• 博客：https://medium.freecodecamp.org/simple-chess-ai-step-by-step-1d55a9266977

• Wiki：https://chessprogramming.wikispaces.com/

AI医疗

33、CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

• 项目主页：https://stanfordmlgroup.github.io/projects/chexnet/

• 论文：https://arxiv.org/abs/1711.05225

• 博客：https://lukeoakdenrayner.wordpress.com/2017/11/18/quick-thoughts-on-chestxray14-performance-claims-and-clinical-tasks/

34、Can you improve lung cancer detection? 2nd place solution for the Data Science Bowl 2017

• Kaggle：https://www.kaggle.com/c/data-science-bowl-2017

• GitHub：https://github.com/dhammack/DSB2017/

• 博客：http://juliandewit.github.io/kaggle-ndsb2017/

35、Improving Palliative Care with Deep Learning

• 项目主页：https://stanfordmlgroup.github.io/projects/improving-palliative-care/

• 论文：https://arxiv.org/abs/1711.06402

36、Heart Disease Diagnosis with Deep Learning

• GitHub：https://github.com/chuckyee/cardiac-segmentation

• 博客：https://blog.insightdatascience.com/heart-disease-diagnosis-with-deep-learning-c2d92c27e730

• 文章：https://chuckyee.github.io/cardiac-segmentation/

![作者：Chuck-Hou Yee(https://upload-images.jianshu.io/upload_images/11573595-6b29a29246a9c066.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240)

AI语音

37、Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model 

• GitHub：https://github.com/Kyubyong/tacotron

• 论文：https://arxiv.org/abs/1703.10135

• 项目主页：https://google.github.io/tacotron/

38、Sequence Modeling with CTC

• GitHub：https://github.com/awni/speech

• 论文：https://distill.pub/2017/ctc/

!作者：Awni Hannun](https://upload-images.jianshu.io/upload_images/11573595-f6b60d1c588e3bb8.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240)

39、Deep Voice: Real-time Neural Text-to-Speech

• GitHub：https://github.com/israelg99/deepvoice

• 论文：https://arxiv.org/abs/1702.07825

• 博客：http://research.baidu.com/deep-voice-production-quality-text-speech-system-constructed-entirely-deep-neural-networks/

40、Deep Learning for Siri’s Voice: On-device Deep Mixture Density Networks for Hybrid Unit Selection Synthesis

• 博客：https://machinelearning.apple.com/2017/08/06/siri-voices.html

AI音乐

41、Computer evolves to generate baroque music!

• 视频：https://www.youtube.com/watch?v=SacogDL_4JU

• 相关博客：http://karpathy.github.io/2015/05/21/rnn-effectiveness/

42、Make your own music with WaveNets: Making a Neural Synthesizer Instrument

• GitHub：https://github.com/tensorflow/magenta/tree/master/magenta/models/nsynth

• 论文：https://arxiv.org/abs/1704.01279

• 博客：https://magenta.tensorflow.org/nsynth-instrument

自然语言处理

43、Learning to communicate: Agents developing their own language

• 博客：https://blog.openai.com/learning-to-communicate/

• 论文：https://arxiv.org/abs/1703.04908

44、Big Picture Machine Learning: Classifying Text with Neural Networks and TensorFlow

• GitHub：https://github.com/dmesquita/understanding_tensorflow_nn

• 博客：https://medium.freecodecamp.org/big-picture-machine-learning-classifying-text-with-neural-networks-and-tensorflow-d94036ac2274

45、A novel approach to neural machine translation 

• GitHub：https://github.com/facebookresearch/fairseq

• 论文：https://arxiv.org/abs/1705.03122

• 博客：https://code.facebook.com/posts/1978007565818999/a-novel-approach-to-neural-machine-translation

46、How to make a racist AI without really trying

• Jupyter Python：https://gist.github.com/rspeer/ef750e7e407e04894cb3b78a82d66aed

• 博客：https://blog.conceptnet.io/2017/07/13/how-to-make-a-racist-ai-without-really-trying/

学习预测

47、Using Machine Learning to Predict Value of Homes On Airbnb

• 博客：https://medium.com/airbnb-engineering/using-machine-learning-to-predict-value-of-homes-on-airbnb-9272d3d4739d

• 中文：https://github.com/xitu/gold-miner/blob/master/TODO/using-machine-learning-to-predict-value-of-homes-on-airbnb.md

48、Engineering Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber

• 论文：https://arxiv.org/abs/1709.01907

• 博客：https://eng.uber.com/neural-networks-uncertainty-estimation/

49、Using Machine Learning to make parking easier

• 博客：https://research.googleblog.com/2017/02/using-machine-learning-to-predict.html

• 产品介绍：https://blog.google/products/maps/know-you-go-parking-difficulty-google-maps/

50、How to Predict Stock Prices Easily — Intro to Deep Learning #7

• 视频：https://www.youtube.com/watch?v=ftMq5ps503w

• 说明：https://github.com/llSourcell/How-to-Predict-Stock-Prices-Easily

• Demo：GitHub：https://github.com/erilyth/DeepLearning-Challenges/tree/master/Image_Classifier

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