7-28 ?7-29
【開源:Scikit-Learn兼容的(Python)半監(jiān)督學(xué)習(xí)框架】"Semi-supervised learning frameworks for Python" GitHub:O網(wǎng)頁鏈接
【蒙特卡羅方法介紹】《Introduction To Monte Carlo Methods》O網(wǎng)頁鏈接? 參閱《蒙特卡羅方法入門》O網(wǎng)頁鏈接
【大腦 vs. 深度學(xué)習(xí) Part I:計算復(fù)雜度】《The Brain vs Deep Learning Part I: Computational Complexity — Or Why the Singularity Is Nowhere Near》O網(wǎng)頁鏈接
【論文:個性化網(wǎng)絡(luò)搜索中對相關(guān)性標簽賦權(quán)的優(yōu)化框架】《An Optimization Framework for Weighting Implicit Relevance Labels for Personalized Web Search》Y Ustinovskiy, G Gusev, P Serdyukov (WWW2015)O網(wǎng)頁鏈接via:OWWW 2015：一個神奇的會議
【幻燈:(D3.js)高效網(wǎng)絡(luò)數(shù)據(jù)可視化指南】《Creating Effective Network Data Visualization》O網(wǎng)頁鏈接
【論文:利用多臂老虎機模型從產(chǎn)品搜索排序中收集額外反饋信息】《Gathering Additional Feedback on Search Results by Multi-Armed Bandits with Respect to Production Ranking》A Vorobev, D Lefortier, G Gusev (WWW2015)O網(wǎng)頁鏈接via:OWWW 2015：一個神奇的會議
【Jeffrey De Fauw的Kaggle diabetic retinopathy競賽參賽記錄&體會&代碼】《Detecting diabetic retinopathy in eye images》O網(wǎng)頁鏈接
【(Python)13行代碼寫神經(jīng)網(wǎng)絡(luò)(Part2 optimizing SGD)】《A Neural Network in 13 lines of Python (Part 2) - Improving our neural network by optimizing Stochastic Gradient Descent》O網(wǎng)頁鏈接Part1:O網(wǎng)頁鏈接
【R/Python數(shù)據(jù)操作基礎(chǔ)】《Data manipulation primitives in R and Python》O網(wǎng)頁鏈接
【(JavaScript)基于圖論的簡單推薦引擎】《Using Graph Theory to Build a Simple Recommendation Engine in JavaScript - Leveraging User Behavior to Drive Recommendations》O網(wǎng)頁鏈接GitHub:O網(wǎng)頁鏈接
【Kaggle's CrowdFlower搜索結(jié)果相關(guān)性競賽第一名訪談】《CrowdFlower Winner's Interview: 1st place, Chenglong Chen》O網(wǎng)頁鏈接
【機器學(xué)習(xí)的可視化介紹(Part1)】《A Visual Introduction to Machine Learning》by R2D3O網(wǎng)頁鏈接
【Chainer下各種優(yōu)化算法(SGD/AdaGrad/RMSprop/ADAM/...)比較】《Chainer Optimizer Comparison》O網(wǎng)頁鏈接
【論文:Ladder Network半監(jiān)督學(xué)習(xí)】《Semi-Supervised Learning with Ladder Network》A Rasmus, H Valpola, M Honkala, M Berglund, T Raiko (2015) MNIST上100標注樣本訓(xùn)練達到1.13%錯誤率O網(wǎng)頁鏈接? Theano/Blocks實現(xiàn)代碼:O網(wǎng)頁鏈接
【(Python)高維數(shù)據(jù)散點圖(Corner plot)繪制工具triangle.py】GitHub:O網(wǎng)頁鏈接
【深度學(xué)習(xí)對抗樣本的誤解與事實】《Deep Learning Adversarial Examples – Clarifying Misconceptions》by Ian Goodfellow [Google]O網(wǎng)頁鏈接? 提供的相關(guān)文章《深度學(xué)習(xí)之對抗樣本問題》O網(wǎng)頁鏈接//@愛可可-愛生活:@CSDN云計算提供的譯文《深度學(xué)習(xí)對抗樣本的八個誤解與事實》O網(wǎng)頁鏈接
【"What's wrong with convolutional neural network" & "Whats wrong with deep learning"】分享兩個有意思的視頻：一個是Geoffrey Hinton去年在MIT的talk：What's wrong with convolutional neural network;另一個是楊立昆(Yann Lecun)在今年CVPR上的talk：Whats wrong with deep learning. 百度網(wǎng)盤：O網(wǎng)頁鏈接
【"Feature engineering is a lot like oxygen. You can't do without it, but you rarely give it much thought"】【免費書:數(shù)據(jù)科學(xué)生存指南】《The Field Guide to Data Science》by Booz Allen Hamilton "Understanding the DNA of Data Science"O網(wǎng)頁鏈接云:O網(wǎng)頁鏈接
【論文:異步隨機優(yōu)化算法擾動迭代分析】《Perturbed Iterate Analysis for Asynchronous Stochastic Optimization》H Mania, X Pan, D Papailiopoulos, B Recht, K Ramchandran, M Jordan (2015)O網(wǎng)頁鏈接
【論文+視頻+Slide+代碼(VM):基于機器學(xué)習(xí)的代碼自動反編譯】《BYTEWEIGHT: Learning to Recognize Functions in Binary Code》O網(wǎng)頁鏈接代碼:O網(wǎng)頁鏈接
【論文:基于文本的音樂自動生成】《Generating Music from Literature》H Davis, S Mohammad (2015)O網(wǎng)頁鏈接Demo:O網(wǎng)頁鏈接《愛可可老師今日視野(15.07.28)》（ 分享自@簡書）O網(wǎng)頁鏈接
【大腦 vs. 深度學(xué)習(xí) Part I:計算復(fù)雜度】《The Brain vs Deep Learning Part I: Computational Complexity — Or Why the Singularity Is Nowhere Near》O網(wǎng)頁鏈接? 此文在 redditO網(wǎng)頁鏈接上引起了熱烈的討論。上月一篇長文O網(wǎng)頁鏈接的作者 jcannell 持相反觀點，但尚未和本文作者 timdettmers 直接辯論。
【關(guān)聯(lián)規(guī)則詳解】《What the heck are Association Rules in Analytics?》O網(wǎng)頁鏈接
【Nick Mills首次參加DrivenData數(shù)據(jù)科學(xué)競賽心得分享】《What I learned from my first data science competition》O網(wǎng)頁鏈接
【"Natural Language Understanding and Prediction Technologies" by Nicolae Duta, IJCAI 2015 TutorialT17】: The Evolution of Natural Language Understanding and Prediction Technologies: from Formal Grammars to Large Scale Machine Learning - Nicolae Duta ijcai-15 tutorial.O網(wǎng)頁鏈接
【基于Spark/MLlib/GraphX的大規(guī)模高效機器學(xué)習(xí)(LR/LDA/FM/DNN/...)平臺Zen】GitHub:O網(wǎng)頁鏈接
【論文:基于中小型計算集群的大規(guī)模主題模型LightLDA】《LightLDA: Big Topic Models on Modest Computer Clusters》J Yuan, F Gao, Q Ho, W Dai, J Wei, X Zheng, E Xing, T Liu, W Ma (WWW2015)O網(wǎng)頁鏈接
【論文:面向非凸優(yōu)化的遞歸分解(IJCAI15杰出論文)】《Recursive Decomposition for Nonconvex Optimization》 A Friesen, P Domingos (IJCAI2015)O網(wǎng)頁鏈接
【Ilya Kavalerov的Kaggle diabetic retinopathy競賽首次參賽體會(ConvNet)】《My 1st Kaggle ConvNet: Getting to 3rd Percentile in 3 months》O網(wǎng)頁鏈接
【IPython notebook教程】《Efficient Data Analysis with the IPython Notebook》 GitHub:O網(wǎng)頁鏈接
【arXiv+Github+Links+Discussion跟蹤論文開源實現(xiàn)的協(xié)同列表網(wǎng)站GitXiv】O網(wǎng)頁鏈接《GitXiv?—?Collaborative Open Computer Science》O網(wǎng)頁鏈接
【Kaggle's CrowdFlower搜索結(jié)果相關(guān)性競賽第一名訪談】《CrowdFlower Winner's Interview: 1st place, Chenglong Chen》O網(wǎng)頁鏈接? 轉(zhuǎn)一發(fā)吧。為了ensemble，前期花了很多時間在代碼重構(gòu)方面，慢慢分離出來preprocessing，feature extraction，model building，model evaluation這個pipeline，這個是挺有幫助的。
【論文+代碼(Java):基于規(guī)則的非特定領(lǐng)域事件抽取框架】《A Domain-independent Rule-based Framework for Event Extraction》MAVEG Hahn, PTHM Surdeanu (ACL2015)O網(wǎng)頁鏈接Code:O網(wǎng)頁鏈接Docs:O網(wǎng)頁鏈接
【詩歌音律拓撲(sonic topology)可視化工具Poemage】O網(wǎng)頁鏈接Paper:O網(wǎng)頁鏈接Code:O網(wǎng)頁鏈接
【高效的Python數(shù)據(jù)分析框架Ibis】O網(wǎng)頁鏈接GitHub:O網(wǎng)頁鏈接通過IPN了解Ibis:O網(wǎng)頁鏈接Slide:《Ibis: Scaling the Python Data Experience》O網(wǎng)頁鏈接云:O網(wǎng)頁鏈接
【論文+代碼:面向網(wǎng)絡(luò)級規(guī)模的并行流標記EM-tree聚類算法】《Parallel Streaming Signature EM-tree: A Clustering Algorithm for Web Scale Applications》C Vries, L Vine, S Geva (WWW2015)O網(wǎng)頁鏈接LMW-tree:O網(wǎng)頁鏈接GitHub:O網(wǎng)頁鏈接【幻燈:(nVIDIA深度學(xué)習(xí)課程)GPU深度學(xué)習(xí)介紹】《Introduction To Deep Learning With GPUs》O網(wǎng)頁鏈接云:O網(wǎng)頁鏈接
【免費書:機器學(xué)習(xí)資源精選匯編】《The Machine Learning Salon Starter Kit》by Jacqueline Isabelle ForienO網(wǎng)頁鏈接云:O網(wǎng)頁鏈接
【可重現(xiàn)數(shù)據(jù)驅(qū)動研究平臺REP】全稱是Reproducible Experiment Platform，統(tǒng)一封裝TMVA, Sklearn, XGBoost, Uboost等分類實現(xiàn)，進行大數(shù)據(jù)集共享一致性對比試驗，可在集群上完成并行訓(xùn)練 GitHub:O網(wǎng)頁鏈接REP(Reproducible Experiment Platform)文檔:O網(wǎng)頁鏈接
【狄利克雷分布/狄利克雷過程筆記】《Notes on the Dirichlet Distribution and Dirichlet Process》O網(wǎng)頁鏈接ipn:O網(wǎng)頁鏈接
《愛可可老師今日視野(15.07.29)》（ 分享自@簡書）O網(wǎng)頁鏈接
