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年终特别献礼之2月热门分享排行

2015年12月19日 21:21 阅读 1359
No 1. 《Distributed Algorithms》
No 2. 《Long Short-Term Memory: Tutorial on LSTM Recurrent Networks》
No 3. 《Introduction to Neural Networks and Machine Learning》
No 4. 《Data Visualization Library》
No 5. 《Machine Learning for Computer Vision》
No 6. 《Tutorial - Python for Data Science》
No 7. 《Getting Started with Spark (in Python)》
No 8. 《The Periodic table of elements for machine learning libraries》
No 9. 《How to Machine Learn》
No 10. 《Human-level control through deep reinforcement learning》
No 11. 《Selecting good features》
No 12. 《A Few Useful Things to Know about Machine Learning》
No 13. [开源] Mariana——开源深度学习框架，基于theano
No 14. 《Creating publication-quality figures with Matplotlib》
No 15. 《Microsoft Malware Classification Challenge (BIG 2015)》
No 16. 《Introduction to Deep Learning with Python》
No 17. [开源] LibRec ——JAVA下的先进推荐算法库
No 18. 《Faster data science - without a cluster: Parallel Programming in R and Python》
No 19. 《What are good ways to get into Computational Linguistics?》
No 20. 《Dealing with Unbalanced Classes ,Svm, Random Forests And Decision Trees In Python》
No 21. 《Deep Learning Summit, San Francisco, 2015》
No 22. 《Python + Elasticsearch. First steps》
No 23. 《A Novel Method for Detecting Plot》
No 24. 《New to Machine Learning? Avoid these three mistakes》
No 25. 《Machine Learning with Scikit-Learn》
No 26. 《Comparison: SGD vs Momentum vs RMSprop vs Momentum+RMSprop》
No 27. [开源] Wiki2Vec —— 从维基百科Dumps生成Word2Vec向量的工具
No 28. 《Scaling Recurrent Neural Network Language Models》
No 29. 《Getting started in data science: My thoughts》
No 30. 《A fast and accurate dependency parser using neural networks》
No 31. 《Caffe-LSTM》
No 32. 《An Introduction to Statistical Learning with Applications in R》
No 33. 《Multi-view Face Detection Using Deep Convolutional Neural Networks》
No 34. 《Text Understanding from Scratch》
No 35. 《I Thought Of Sharing These 7 Machine Learning Concepts With You》
No 36. 《The 35-hour Workweek with Python》
No 37. [开源] mlxtend —— Python的数据科学（数据分析&机器学习）工具和扩展库
No 38. 《GET STARTED IN R》
No 39. [IPN] NLP-in-Python —— 介绍Python下NLP的系列ipn
No 40. 《Why you should start by learning data visualization and manipulation》
No 41. 《Introduction to Conditional Random Fields》
No 42. [开源]  Kayak —— Harvard的Python深度神经网络快速原型库
No 43. 重点推荐！LeCun：The Unreasonable Effectiveness of Deep ...
No 44. 《STREAM PROCESSING, EVENT SOURCING, REACTIVE, CEP… AND MAKING SENSE OF IT ALL》
No 45. 《Stream Processing and Probabilistic Methods: Data at Scale》
No 46. 《Reinforcement Learning》
No 47. 《From feature descriptors to deep learning: 20 years of computer vision》
No 48. 《Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift》
No 49. 《Recommender Systems: Super Overview》
No 50. 《Ten Lessons Learned from Building (real-life impactful) Machine Learning Systems》

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HippoMatrix
@有道云笔记 °年终特别献礼之2月热门分享排行 ​​​​
2015-12-20 01:10 来自 iPhone 6 Plus
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不止鱼
老师辛苦了[心][心][心] °年终特别献礼之2月热门分享排行 ​​​​
2015-12-20 00:33 来自 iPhone 6s Plus

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