Angel \”Java\” Lopez on Blog

November 11, 2011

Machine Learning: Links, News and Resources (1)

Filed under: Artificial Intelligence, Lambda Calculus, Links, Machine Learning — ajlopez @ 10:01 am

http://en.wikipedia.org/wiki/Machine_learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases. Machine learning is concerned with the development of algorithms allowing the machine to learn via inductive inference based on observing data that represents incomplete information about statistical phenomenon and generalize it to rules and make predictions on missing attributes or future data. An important task of machine learning is classification, which is also referred to as pattern recognition, in which machines “learn” to automatically recognize complex patterns, to distinguish between exemplars based on their different patterns, and to make intelligent predictions on their class.

Machine Learning at Stanford
http://www.ml-class.org/course/auth/welcome
Enroll today in our online class for free!

Reinforcement Learning: An Introduction
http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html

Machine Learning
Systems that Improve Their Performance
http://aaai.org/AITopics/MachineLearning

Does Machine Learning Really Work?
http://www.aaai.org/ojs/index.php/aimagazine/article/view/1303/1204

My first encounter with the topic:
Samuel’s Checkers Player
http://webdocs.cs.ualberta.ca/~sutton/book/ebook/node109.html

TD Gammon
http://webdocs.cs.ualberta.ca/~sutton/book/ebook/node108.html

University of Alberta, Department of Computing Science, Machine Learning
https://www.cs.ualberta.ca/research/research-areas/machine-learning

University of Alberta, CS, Research
https://www.cs.ualberta.ca/research
See
https://www.cs.ualberta.ca/research/research-areas/bioinformatics
https://www.cs.ualberta.ca/research/research-areas/computer-games
https://www.cs.ualberta.ca/research/research-areas/artificial-intelligence
https://www.cs.ualberta.ca/research/research-areas/advanced-man-machine-interfaces

Turing award goes to ‘machine learning’ expert
http://www.physorg.com/news/2011-03-turing-award-machine-expert.html

Stanford School of Engineering – Stanford Engineering Everywhere
http://see.stanford.edu/see/courseInfo.aspx?coll=348ca38a-3a6d-4052-937d-cb017338d7b1

InfoQ: Machine Learning: A Love Story
http://www.infoq.com/presentations/Machine-Learning

Informaniac: Machine Learning for Bug Discovery
http://www.informaniac.net/2008/06/machine-learning-for-bug-discovery.html

io9. We come from the future.
http://m.io9.com/5659503/a-computer-learns-the-hard-way-by-reading-the-internet

bradford’s infer at master – GitHub
http://github.com/bradford/infer

Pragmatic Programming Techniques: Map/Reduce to recommend people connection
http://horicky.blogspot.com/2010/08/mapreduce-to-recommend-people.html

Smarter Than You Think – I.B.M.’s Supercomputer to Challenge ‘Jeopardy!’ Champions – NYTimes.com
http://www.nytimes.com/2010/06/20/magazine/20Computer-t.html?hp

Google Prediction API: Commoditization of Large-Scale Machine Learning? – A Computer Scientist in a Business School
http://behind-the-enemy-lines.blogspot.com/2010/05/google-prediction-api-commoditization.html

Apache Mahout – Overview
http://mahout.apache.org/

Papers – Hadoop Wiki
http://wiki.apache.org/hadoop/Papers

20Q – Wikipedia, the free encyclopedia
http://en.wikipedia.org/wiki/20Q

Machine Learning in Game AI – Stack Overflow
http://stackoverflow.com/questions/970060/machine-learning-in-game-ai

Applications of Machine Learning to the Game of Go
http://videolectures.net/epsrcws08_stern_aml/
David Stern, Applied Games Group, Microsoft Research Cambridge

Deep Boltzmann Machine on MNIST
http://quotenil.com/Deep-Boltzmann-Machine-on-MNIST.html

Introduction to MGL (part 1)
http://quotenil.com/Introduction-to-MGL-(part-1).html

Measuring Measures – blog – Learning about Machine Learning, 2nd Ed.
http://measuringmeasures.com/blog/2010/3/12/learning-about-machine-learning-2nd-ed.html

IET/BCS Turing Lecture 2010 | Professor Christopher Bishop
http://tv.theiet.org/technology/infopro/turing-2010.cfm

So you think machine learning is boring?
http://www.causata.com/blog/2010/02/so-you-think-machine-learning-is-boring.html

Google AI Challenge
http://csclub.uwaterloo.ca/contest/

Common Lisp and Google AI Challenge
http://aerique.blogspot.com/2010/02/google-ai-challenge-2010.html

Infer.NET: Building Software with Intelligence :: Sessions :: Microsoft PDC09
http://microsoftpdc.com/Sessions/VTL03

Infer.NET – Now with F# support @ JustinLee.sg
http://www.justinlee.sg/2009/12/09/infer-net-now-with-f-support/

Pragmatic Programming Techniques: Machine Learning: Association Rule
http://horicky.blogspot.com/2009/10/machine-learning-association-rule.html

Pragmatic Programming Techniques: Machine Learning with Linear Model
http://horicky.blogspot.com/2009/11/machine-learning-with-linear-model.html

A New Theory of Awesomeness and Miracles, by James Bridle, concerning Charles Babbage, Heath Robinson, MENACE and MAGE
http://shorttermmemoryloss.com/menace/

A small personal project to learn Clojure by implementing some simple machine learning algorithms edit
http://github.com/mreid/injuce/

Introducing Apache Mahout
http://www.ibm.com/developerworks/java/library/j-mahout/index.html

Apache Mahout – Overview
http://lucene.apache.org/mahout/

How Flightcaster squeezed predictions from flight data
http://www.datawrangling.com/how-flightcaster-squeezes-predictions-from-flight-data

Map-Reduce for Machine Learning on Multicore
http://www.cs.stanford.edu/people/ang//papers/nips06-mapreducemulticore.pdf

Torch3: The Dream Comes True
http://www.torch.ch/introduction.php

Reinforcement Learning and Artificial Intelligence: Toolkit
http://rlai.cs.ualberta.ca/RLAI/RLtoolkit/RLtoolkit1.0.html

Machine Learning Book Code
http://seat.massey.ac.nz/personal/s.r.marsland/MLBook.html

Scientific Commons: Simon Colton
http://de.scientificcommons.org/simon_colton

A Grid-based Application of machine learning to model generation
http://www.doc.ic.ac.uk/~sgc/papers/sorge_ki04.pdf

Reinforcement Learning: An Introduction
http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html

Learning Draughts/Checkers
http://www.codeproject.com/KB/game/learning_draughts.aspx

Learning Connect Four
http://www.codeproject.com/KB/game/learningconnectfour.aspx

Introduction to Machine Learning
http://robotics.stanford.edu/~nilsson/mlbook.html

The Use of Java in Machine Learning
http://www.developer.com/java/other/article.php/10936_1559871_1

Similarity Learning – IDL – EE – Washington.edu
http://idl.ee.washington.edu/similaritylearning/

Gwap
http://www.gwap.com/gwap/about/

Machine Learning
http://aima.cs.berkeley.edu/ai.html#learning

Artificial Intelligence on the Web
http://aima.cs.berkeley.edu/ai.html
This page links to 820 pages around the web with information on Artificial Intelligence.

Yu-Han Chang
http://www.yuhanchang.com/home.html
“My research centers on learning in rich multi-agent environments”

My Links
http://www.delicious.com/ajlopez/machinelearning

Angel “IAmStillLearning” Lopez
http://www.ajlopez.com
http://twitter.com/ajlopez

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