This post is planned to be an ongoing thought process. I’ve used Matlab when doing my MSc in Intelligent Systems and Robotics at De Montfort University Centre for Computational Intelligence. When I started using it I thought ‘wow this is cutting edge’ and enjoyed using it (apart from constant alt-tab between windows). So far I’ve used Matlab for:
- Developing (and teaching) Fuzzy Log, both GUI and code
- Developing (and teaching) Artificial Neural Networks (Perceptron, Pattern Net, etc) using the KDD 1999 Network Data
- Robotics Simulation (iRobot Create)
Work in progress
As part of my work I am looking at statistical models in the health care sector, specifically dealing with data around Heart Failure. To test and demonstrate some of the statistical models I have used Open Source data from the UCI Machine Learning Repository. For the examples below I am using the Cleveland set with all unknown values (?) set to zero.
Over the summer I’ve been using Python for Machine Learning (ML), specifically state representation of an Atari 2600 game emulator. The project initially started with looking at this paper  which developed agents using Theano which then lead to me using the Anaconda Python package.
The package is great as it comes ready with everything most people would need to get started in Data Analysis and ML. As an example it comes ready with…
- Python 2.7 (3.x also available)
- Scikit Learn
- iPython Notebook