Herself’s Artificial Intelligence

Can’t do much with machine learning and artificial intelligence with out data so I started to put together a list of free online sources of data:

Spam Assassin Public Corpus
The Official WhitePages
Blekko
National Weather Service
Infochimps
OpenStreetMap
Yahoo! Finance
Google Books
Census Bureau Home Page
Bureau of Labor Statistics Home Page
Welcome to Infomine: Scholarly Internet Resource Collections
NewsLibrary.com
American Religion Data Archive
Demographia
Government Web Resources
MedlinePlus
Internet Archive
Clark Library
Household Products Database
Econo data
St. Louis Fed: Economic Research
National Bureau of Economic Research
Fed Stats
Supreme Court
Complete Planet
Iowa Electronic Markets
Tax stats
GSS General Social Survey
PMC Biomedical and Life Sciences Journal Literature
Google’s Ngram Viewer

Human Computer Interfaces
Game Theory
Probabilistic Graphical Models
Computer Science 101
Software as a Service
Machine Learning
Natural Language Processing
Cryptography
Design and Analysis of Algorithms I
and
Lean Launchpad
Technology Entrepreneurship

I can’t recommend these classes enough. I’ve taken the iPhone Development, Intro to Artificial Intelligence, Intro to Databases, and Machine Learning classes.

It’s my thought that the future of education will not be 4 year degrees on site, but life long learning at home.

If you need to brush up on some math first try Khan Academy, Wolfram Math World.

Octave (download)

Install Octave per directions.
To start Octave from a command line create the following file and place it with permissions 755 in /user/local/bin

file name: Octave
#!/bin/bash
open /Applications/Octave.app

Next edit /Applications/Octave.app/Contents/Resources/bin/mkoctfile
Add these lines to the bottom of the file:
# fixes to make gnuplot behave
CFLAGS=”-m32 ${CFLAGS}”
FFLAGS=”-m32 ${FFLAGS}”
CPPFLAGS=”-m32 ${CPPFLAGS}”
CXXFLAGS=”-m32 ${CXXFLAGS}”
LDFLAGS=”-m32 ${LDFLAGS}”

GNU Plot (download)

Install per directions.
Edit the file /Applications/Gnuplot.app/Contents/Resources/bin/gnuplot
Edit the 5th and 6th lines below and save

# Setting up various path information variables that are needed to
# startup the Gnuplot program.
GNUPLOT_HOME=”${ROOT}”
PATH=”${ROOT}/bin:${PATH}”
# DYLD_LIBRARY_PATH=”${ROOT}/lib:${DYLD_LIBRARY_PATH}”
DYLD_LIBRARY_PATH=”${ROOT}/lib”
DYLD_FRAMEWORK_PATH=”${ROOT}/lib:${DYLD_FRAMEWORK_PATH}”

More information:
Stack Overflow directions to fix GNUPlot to work with Octave on OSX

Stanford is offering free online classes in Machine Learning and Introduction to Artificial Intelligence

I’ve taken their iPhone programming class and it was fantastic. I’m going to take the AI class to brush up on things and the Machine Learning to learn some new things.

Classes begin Oct 10 and run through mid Dec 2011.

A Twitter friend working in artificial intelligence clued me into this cool open source project that’s just getting going.

Stephen Larson has a talk on Evolving AI: Lt. Data will be Born from Artificial Worms, you can watch the talk on YouTube.. There is a virtual worm project on Caltech

The general idea is to start with a digital form of a simple life form and evolve it into a general intelligence much as we have evolved from simple origins. Unlike the real world the computer can run through millions of evolutions in a very short time.

An open source project openworm has been started. You’ll find source code and demos there.

To bring you up to speed on worms you’ll want to dig through C. Elegans II an online textbook on C. elegans.

Also you’ll want to dig into WebGL which is used to create the 3D world demos.