"Open source tools have recently reached a level of maturity which makes them suitable for building large-scale real-world systems. At the same time, the field of machine learning has developed a large body of powerful learning algorithms for a wide range of applications. Inspired by similar efforts in bioinformatics (BOSC) or statistics (useR), our aim is to build a forum for open source software in machine learning."

"We are trying to do for machine learning what Image Magick has done for image processing. That is, we try to keep it simple by providing a big range of functionality in the form of easy-to-use command-line tools. You are free to mix tools from other packages in with ours. You are free to mix your own custom tools with ours. You are free to write scripts that automate your experiments. You are free to use our tools in ways that we could not foresee."

Amazing. The machine learning that has gone into allowing ppl to own remixes - this thing reverse engineers a mix into component parts, allow you, as the listener to buy the parts, then reconstructs it for you, using your personal right to remix.

a growth industry: automating the production of journalism, books, textual content

includes lots of tasty goodies radiating out from the SVM core, such as generalised markovian model learning, HDF5, string kernels, multi-language bindings and an emphasis on scalability.

it is not enough to have a language for specifying your prior structural beliefs—instead we must have a language for such which results in computationally tractable solutions.

mapreduce alternative thingy for distributed nodes

"And while it may seem crass and anti-intellectual to consider a financial measure of success, it is worth noting that the intellectual offspring of Shannon's theory create several trillion dollars of revenue each year, while the offspring of Chomsky's theories generate well under a billion."

mlpy is a high-performance Python package for predictive modeling. It makes extensive use of NumPy (http://scipy.org) to provide fast N-dimensional array manipulation and easy integration of C code. mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification, regression and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. The package includes tools to measure stability in sets of ranked feature lists.

Markov Logic Networks (MLNs) is a framework that combines statistical and logical reasoning; they have been applied to many data intensive problems including information extraction, entity resolution, text mining, and natural language processing....
...The current version (0.2) of Tuffy is capable of the following MLN tasks:
MAP inference, where we want to find out the most likely possible world;Marginal inference, where we want to estimate marginal probabilities;Weight learning, where we want to learn the weights of MLN rules given training data.Furthermore, Tuffy provides the following functionalities beyond the realm of MLNs:
Datalog: In addition to MLN rules, you can also execute Datalog rules in Tuffy.Functions: Tuffy comes with a library of common numeric/string/boolean functions, which can be used inside an MLN rule. In particular, you can perform arithmetic manipulation and comparison in MLN rules.

what it says

The Clever Algorithms project is an effort to describe a large number of algorithmic techniques from the the field of Artificial Intelligence in a complete, consistent, and centralized manner such that they are accessible, usable, and understandable.

The Clever Algorithms project is currently hosted online at http://www.CleverAlgorithms.com

This is a repository for the Clever Algorithms: Nature-Inspired Programming Recipes project for hosting, versioning, and collaboration, used during the development of the content for deliverables (website and book), as well as for the ongoing maintenance of the outcomes from the project.

machine learning in python, courtesy NICTA again

sweet looking machine learning toolchain for python

statiscial analysis on your database contents: "MADlib is an open-source library for scalable in-database analytics. It provides data-parallel implementations of mathematical, statistical and machine learning methods for structured and unstructured data". Seems to be largely in PL/C, with some bonus python on the front.

"The SOAR project was started at CMU by Newell, Laird and Rosenbloom as a testbed for Newell's theories of cognition.

Keeping with Newell's definition of intelligence as the ability to use ones knowledge to achieve ones goals, SOAR was designed to use all of its knowledge on each problem. There is one main memory structure into which all long-term memories are to fit. All queries use all of it."

"k-means clustering, hierarchical clustering and self-organizing maps"

designed for genetic data, but no reason to stick to that. perl, python, c, c++ bindings.

alternative take on the genetic search technique designed to mimic the behaviours of improvising musicians rather than the success and failues of genotypes. Sounds interesting both as a technique and a model.

All the buzzwords I do at once.

coding for semi intelligent agents for the "non programmer".

user interface crowdsourcing New Media porn

it's the page of that trendy work-out-your-laws-for-you package

open computer vision library. originally spawned by IBM and now released into the world for realtime blob mangling and smooth lattice deformation fun.

The Agent-based computational Economics mothership is truly here. Tesfatsion ♥♥♥

aging but provocative list of evolutionary art projects, well curated but without analysis.

"This is a genetic programming system based on the idea of using a kind of grammar as the underlying gene. Grammars are stored in a raw format, then parsed into productions. Those productions are expanded. The resulting strings are then evaluated (usually in a kind of basic stack machine) and the evaluations rated and evolved.

This version is rather raw. It is usable pretty much only by someone who wants to hack around in the innards - it is probably completely unusable by anyone who is not a java programmer at the moment. The GUI works for me (more or less - there are a few oddities having to do with the way and when it redisplays) but then I'm more interested in playing with the code and the evolutionary process than with building a pretty gui. Comments about the ugliness of the code will be cheerfully ignored"

bigger, enterprisier, buzzwordier python evolutionary library. seems pure GA as opp GP, but with tasty operators, visualisation, and parallelisation support

the only DVCS python GP library. pity it looks dead.

wow, the whole conference proceedings are online and there are some ripper papers in there

"Answer Factory: A system for pragmatic genetic programming projects"

include turing complete DSL, image processing and so on

highest linked-GP toolkit has unspecified link to groovy. Is that the adjective or the noun, i'd like to know? Anyway, it's dead since 2006, so this link is purely so that i can remember *not* to use it.

SVM, bayesian, neural etc learning algorithms for python+scipy

actually evolving rules in an agent based model. good times.

simple, good but unmaintained, VCS-less python genetic programming library. A pity; it looks like the lightest most pythonic one IMO.

learning in the game-theoretic statistical framework of vovk and shafer

deletes all the music from your library which is not cool enough for you

open  source python genetic algorithm frameowrk

forum for machine learning types

"Peach is a pure-python module, based on SciPy and NumPy to implement algorithms for computational intelligence and machine learning. Methods implemented include, but are not limited to, artificial neural networks, fuzzy logic, genetic algorithms, swarm intelligence and much more."

O'reilly gives an overview of large dataset tools, including some nice machine learning ones

Fun looking ideas and futures blog, with many eminent figures aggregatd - John Sterman, Brian Arthur et al

a sketch of the process of learning the human face manifold by google

a sketch of the process of learning the human face manifold by google

python's hottest latest computer vision library is hot lately

awesome analog hack: an AI that learns noughts-and-crosses, made out of matchboxes and beans

the combination of all christmas season songs into one ungodly mutant offspring.

Instant guid to getting started with machine learning

This is the single thing that I am glad to take away uncritically from Shirky - slices through the assumptions of AI-we-can-taxonomise-the-world folks in the semantic web camp.

a feed reader that gives you feeds on *topics* you suggest, rather than from feeds you request. Looks like a handly breaking-news-filter, and comes recommended, but have not yet tried it myself.

Science NSW should get in to THIS.

There are two ways to have a fast learning algorithm: (a) start with a slow algorithm and speed it up, or (b) build an intrinsically fast learning algorithm. This project is about approach (b), and it's reached a state where it may be useful to others as a platform for research and experimentation.

There are two algorithms, one implementing specialist gradient descent (GD) on squared loss and the other implementing specialist exponentiated gradient descent (SEG) on squared loss.

image classification using SOM in python

a semantic wiki in the anglo-american school - accepts formally verified proofs, includes automatic theorem provers and assistants, ajax theorem completion... Well, in principle. Looks like it hasn't launched yet.

computer vision library from ibm. thanks guys.

REST-driven online semantic database, plugging into all kinds of neato visualisers and nodebox and that. currently a bit populated by spammy folks.

a whole bunch of machine learning tutes from some folks who went on to form a google campus

a software package for your mac that learns about who you are and what you are doing so i can reconfigure your environment for you. think of the potential for productivity. think also how disastrous privacy violations will be in the future when this shit is commonplace.

genetic computing, what hath thou wrought?

the various uses of social by military organisations of social networking apps are pretty well known. What's news to me is how rich the ecology of those applications has become. I wonder if facebook has AI knowledge management applications?

another strange branch of the language evolution tree - casting aside lambda calculus as a model in favour of term-rewriting, with a dusting of JIT, introspection, symbolic computation

sniff the global zeitgeist via twitter

insane. search for songs by lyrics or by pitch tracking your humming and matching against melodies. oh, and it works on your iphone.

OOP 3d multi agent simulations with python chops.

classic. classic. the long and short of it (ahem) is that the universe is a twos-complement architecture

make fly-throughs from photos

Web 2.008

sexy robots come for your wallet. thx strangefeatures.

hidden markov toopic models for text analysis

API for calling humans: "Amazon Mechanical Turk provides a web services API for computers to integrate "artificial artificial intelligence" directly into their processing by making requests of humans. Developers use the Amazon Mechanical Turk web service

LeafRSS - The Learning Filtered RSS Aggregator: A simple RSS aggregator that learns to filter out unwanted articles from multiple feeds automatically. Written in PHP, LeafRSS is ideal for presentation of aggregated and filtered RSS text on a web site.

web2.0 janus node?

mr emobied cognition is digitally loquacious

The KLI Theory Lab is a comprehensive bio- and bibliographical data base covering eighteen research areas related to evolution and cognition research. The primary aim of the KLI Theory Lab is to foster interdisciplinarity by highlighting thematic intercon