What are some good resources for learning about machine learning? Why

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What are some good resources for learning about machine learning? Why

Prerequisites

  • Before you get to think about algorithms look carefully at the data and select all the relevant features to include in your model. See this talk by Jeremy Howard : At Kaggle, It’s a Disadvantage To Know Too Much
  • Kick-start your pattern recognition career by learning about Decision Trees andRandom Forests , they seem to work well in practice. See Decision Trees: What are some good resources for learning about decision trees?
  • Good places for practice are Digit Recognizer and UCI Machine Learning Repository

Lecture Notes:
  • Sebastian Thrun, CS373: http://www.udacity.com/overview/...
  • Alina Beygelzimer, COMS4771:  http://hunch.net/~coms-4771/lect...
  • Cosma Shalizi, 35-350:http://www.stat.cmu.edu/~cshaliz...
  • Cosma Shalizi, 36-350: http://www.stat.cmu.edu/~cshaliz...
  • Cosma Shalizi, 36-402: http://www.stat.cmu.edu/~cshaliz...
  • Andrew Ng, CS229: http://www.stanford.edu/class/cs... , http://see.stanford.edu/see/lect...
  • Andrew Ng, CS294: http://www.stanford.edu/class/cs...
  • Chris Volinsky, COMS4240http://www2.research.att.com/~vo...
  • Milos Hauskrecht, CS3750: http://www.cs.pitt.edu/~milos/co...
  • S V N Vishwanathan, CS590: http://www.stat.purdue.edu/~vish...
  • Dan Roth, CS446: http://l2r.cs.uiuc.edu/~danr/Tea...
  • Tony Jebara, COMS4771: http://www.cs.columbia.edu/~jeba...
  • Tony Jebara, COMS6772: http://www.cs.columbia.edu/~jeba...
  • Michael I. Jordan, CS294: http://www.cs.berkeley.edu/~jord...
  • Carlsos Guestrin, CS10701: http://www.cs.cmu.edu/~guestrin/...
  • Tom Mitchell, CS10701: http://www.cs.cmu.edu/~tom/10701...
  • Eric Xing, 10708: http://www.cs.cmu.edu/~epxing/Cl...
  • Yoav Freund, CSE254: http://seed.ucsd.edu/mediawiki/i...
  • Roni Rosenfeld, 11761: http://www.cs.cmu.edu/~roni/11761/
  • Sanjiv Kumar, EECS6898: http://www.sanjivk.com/EECS6898/...
  • Collins, COMS6998: http://www.cs.columbia.edu/~mcol...
  • Radford M. Neal, CSC 2541: http://www.cs.utoronto.ca/~radfo...
  • Jaakkola & Collins, 6.867: http://courses.csail.mit.edu/6.8...
  • Hamilton, CS831: http://www2.cs.uregina.ca/~hamil...
  • Girolami, MLM: http://www.dcs.gla.ac.uk/~girola...
  • Bengio, IC-49: http://bengio.abracadoudou.com/l...
  • Bottou, COS424: http://www.cs.princeton.edu/cour...
  • Lin, CMSC838: http://www.umiacs.umd.edu/~jimmy...
  • Charikar, CS493: http://www.cs.princeton.edu/cour...
  • Kelner, 18-409, http://ocw.mit.edu/courses/mathe...
  • Spielman, 500A: http://www.cs.yale.edu/homes/spi...
  • Joachims, CS6784: http://www.cs.cornell.edu/Course...
  • Joachims, CS4780: http://www.cs.cornell.edu/Course...
  • Hinton, CSC2535: http://www.cs.toronto.edu/~hinto...
  • Kakade & Shakhnarovich, CMSC 3590: http://ttic.uchicago.edu/~gregor...
  • Khardon, 150AML: http://www.cs.tufts.edu/~roni/Te...
  • Poggio, Rosasco, Frogner & Mallapragada, 9.520: http://www.mit.edu/~9.520/
  • Lavie & Frederking,11-711: http://www.cs.cmu.edu/afs/cs.cmu...
  • Hofman, DDM: http://jakehofman.com/ddm/
  • Smola, C281B: http://alex.smola.org/teaching/b...
  • Abu-Mostafa, CS156: http://www.youtube.com/playlist?...
  • Mohri, CSCI-GA.2566-001: http://www.cs.nyu.edu/~mohri/ml12/
  • Rakhlin & Sridharan: STAT 928, Spring 2012 (thanks to Justin Rising)
  • Ryan Adams, Harvard CS181 -- Intelligent Machines: Perception, Learning, and Uncertainty
  • Peter Bartlett at UC Berkeley (also the 2006 version)
  • Sham Kakade and Ambuj Tewari at TTI, UChicago
  • Maxim Raginsky at Duke
  • Shai Shalev-Shwartz at Hebrew U.
  • Dmitry Panchenko at MIT
  • A Course in Machine Learning by Hal Daumé III

Getting Started
  • Machine Learning: What are some good learning projects to teach oneself about machine learning?
  • Programming Challenges: What are some good "toy problems" in data science?
  • Career Advice: How do I become a data scientist?
  • Machine Learning: What are some good class projects for machine learning using MapReduce?
  • Large Scale Learning: What are some introductory resources for learning about large scale machine learning? Why?
  • How do I start with Machine Learning? http://news.ycombinator.com/item...

Textbooks:
  • There aren't many good introductory books on ML, probably Tom Mitchell's is one of the best for starters: http://www.cs.cmu.edu/afs/cs.cmu...
  • For hands-on guides see Quinlan's C4.5: http://www.amazon.com/C4-5-Progr...  and Marsland's ML from Algorithmic Perspective: http://www.amazon.com/Machine-Le...
  • Before you get to PRML (the most popular ML textbook http://research.microsoft.com/en... ) try reading earlier works by Bishop to get into his head. This one is excellent:  http://www.amazon.com/Neural-Net... and also the old edition of Duda & Hart: http://www.amazon.com/Pattern-Cl...
  • Breiman, Leo; Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and regression trees.
  • Hastie, T., Tibshirani, R., Friedman, J. H. (2001). The elements of statistical learning : Data mining, inference, and prediction: http://www-stat.stanford.edu/~ti...
  • David MacKay, Information Theory, Inference, and Learning Algorithms:http://www.inference.phy.cam.ac....
  • Boosting: Foundations and Algorithms (Adaptive Computation and Machine Learning series): Robert E. Schapire, Yoav Freund: 9780262017183: Amazon.com: Books
  • Amazon.com: Statistical Pattern Recognition (9780470682272): Andrew R. Webb, Keith D. Copsey: Books 
  • David Barber, Bayesian Reasoning and Machine  Learning:http://www0.cs.ucl.ac.uk/staff/d...
  • What are some alternatives to Bishop's PRML textbook?
  • Metaoptimize, Good Freely Available Textbooks on ML: 
    http://metaoptimize.com/qa/quest...

Data Repositories
  • Data: Where can I find large datasets open to the public
  • Data: What are some free, public data sets?

Conferences & journals
  • Machine Learning: What are the top publishing venues in the machine learning field?

People & Communities
  • Blogs: http://metaoptimize.com/qa/quest...
  • Metaoptimize,  Stackoverflow, Quora, Mahout mailing list
  • Graduate School: What are the best graduate schools for studying machine learning?
  • http://www.reddit.com/r/MachineL...
  • http://stackoverflow.com/questio...
  • http://www.delicious.com/machine...
  • http://twitter.com/chrisalbon/da...
  • hunch.net

Q&A
  • Information Retrieval: What are some good resources to get started with Information Retrieval? Why?
  • Mathematical Optimization: What are some good resources to learn about optimization?
  • What are some good resources for learning about numerical analysis?
  • Statistics (academic discipline): What are some good resources for learning about statistical analysis?
  • What are some recent texts on kernel methods?
  • Machine Learning: What are some good resources for learning about dimensionality reduction? Why?
  • Why the current obsession with "big" data?
  • Machine Learning: What papers have shown that for machine learning, data set size is more important than the model being trained?
  • What is the difference between statistics and machine learning?
  • Machine Learning: How can you learn Mathematics for machine learning?
  • What is the best book for learning neural networks?
  • Stream Processing: What are some good resources for learning about stream mining? Why?
  • Which data stream mining tools can handle Big Data?
  • Machine Learning: What resources on graphical models are recommended for machine learning students wanting to enter the field?
  • What are some benefits and drawbacks of discriminative and generative models?
  • Hidden Markov Models: Hidden Markov Models: What are some good resources for learning about Hidden Markov Models?
  • What are some good resources to learn about Gaussian Process Models?
  • Vector Space Models: What are some open-source implementations of vector space models?
  • What is a good source for learning about Bayesian networks?
  • What are the best books on network theory
  • Natural Language Processing: What are some good resources for getting started learning about natural language processing?
  • Natural Language Processing: NLP and machine learning tools: Buy or build?
  • Natural Language Processing: What are the most important research papers which all NLP students should definitely read?
  • Natural Language Processing: What are some ways I can test the error of applying a topic model to tweets, given that there is no known corpus of topic labels?
  • Natural Language Processing: What is the best approach for text categorization?
  • Quora PeopleRank: What are some existing "PeopleRank" algorithms?
  • How does one determine similarity between people online?
  • What are the top 10 data mining or machine learning algorithms?
  • Apache Mahout: What are some important algorithms not yet covered in Mahout?
  • Recommendation Systems: What are some good research papers and articles on recommendation systems and engines?
  • Support Vector Machines: What SVM package is best for large-scale linear classification?
  • What is the best way for a math Ph.D. to start a career in a data driven start up?
  • Machine Learning: What are some good machine learning packages/softwares?
  • Compressed Sensing: What are some good resources for learning about compressed sensing?
  • What are the advantages of different classification algorithms?
  • Computer Science Research: What are some good resources for learning about stochastic optimization?
  • Computer Vision: What are some good resources for learning about computer vision?
  • Computational Genomics: What are some good resources for learning about computational genomics? Why?
  • Decision Trees: What are some good resources for learning about decision trees?
  • Why does deep learning require the construction of generative data models?
  • Why are spreadsheet champions considered to be expert data analysts while computer science majors take a back seat?
  • Machine Learning: What skills are needed for machine learning jobs?
  • Assuming you have all the online data of all the people in the world (say, email, FB, IM, sms, call information), what are some interesting questions that could potentially be answered?
  • Reputation Systems: What are the seminal papers on reputation systems?
  • Microsoft Research: What products have come out of Microsoft Research?
  • Are there any cool hacks for Kinect?
  • What are the lessons from the Netflix Prize challenge?
  • What new innovations have occurred in the field of artificial intelligence from 2000 to 2010?
  • Computer Science Research: Which CS areas have the most low-hanging fruit for research?
  • What are the best resources to learn about online algorithms?
  • Artificial Neural Networks: What are some neural network architectures?
  • http://www.quora.com/Natural-Lan...
  • http://www.quora.com/Machine-Lea...

Other    
  • Hu, How Khan Academy is using Machine Learning to Assess Student Mastery: 
    http://david-hu.com/2011/11/02/h...
  • Dziuba, Machine Learning Is Not As Cool As It Sounds: http://teddziuba.com/2008/05/mac...
  • Shalizi, Learning Theory: http://cscs.umich.edu/~crshalizi...
  • Gabrilovich, ML links: http://www.cs.technion.ac.il/~ga...
  • Scott, ML bibliography: http://www.eecs.umich.edu/~cscot...
  • Aha, ML resources (a bit outdated): http://home.earthlink.net/~dwaha...
  • Bennett et al., The Interplay of Optimization and ML: http://jmlr.csail.mit.edu/papers...
  • Popular Text classification algorithms: http://answers.google.com/answer...
  • http://www.gaussianprocess.org/
  • http://www.kernel-machines.org/
  • http://decisiontrees.net/
  • http://deeplearning.net/
  • http://active-learning.net/
  • http://www.cse.unsw.edu.au/~bill...
  • http://www.mdl-research.org/read...
  • http://www.dai-labor.de/carr2011...
  • http://www.cs.utah.edu/~hal/searn/
  • http://learning.cis.upenn.edu/co...

  • http://snowbird.djvuzone.org/201...
  • http://scikit-learn.sourceforge....
  • http://www.graphlab.ml.cmu.edu/
  • http://mlss11.bordeaux.inria.fr/...
  • http://googleresearch.blogspot.c...

  • https://github.com/ogrisel/sciki...
  • http://metaoptimize.com/qa/quest...

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