Herself’s Artificial Intelligence

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

Cuckoos have an aggressive reproduction strategy that involves the female laying her fertilised eggs in the nest of another species so that the surrogate parents unwittingly raise her brood. Sometimes the cuckoo’s egg in the nest is discovered and the surrogate parents throw it out or abandon the nest and start their own brood elsewhere.

The team base their design search on three simple principles that emerge from the cuckoo’s strategy:

* First, each cuckoo lays one egg (a design solution) at a time, and dumps it in a randomly chosen nest.
* Second, the best nests with a high quality egg (better solution) carry over to the next generation.
* Third, the number of available host nests is fixed, and a host and there is a finite probability of the cuckoo in the nest being discovered.

The team have encapsulated these three principles in a mathematical formula that they then converted to computer software code. The various design parameters and constraints are fed to the software, which tests each “egg” discarding some based on lack of fitness and sending the successful solutions through a second round and so on until an optimal solution emerges.

The team has carried out standard mathematical design tests on their cuckoo search, which itself has now been optimised and also compared it with particle swarm optimisation and other techniques to show that it is more efficient than these other approaches to engineering design of a welded beam and a spring, two key engineering components of many structures. Read more

More information:
Engineering Optimisation by Cuckoo Search ( arXiv paper )
Other papers by Xin-She Yang