Block Practical: Connectionist Models and Cognitive Processes
1st Week: Introduction to Programming and Connectionist Networks
- Code: pyceptron.py
- Slides: Part 1: Intro to Programming, Part 2: Intro to Networks
- Exercises: Pyceptron
2nd Week: Going from Two Network Layers to Three
- Code: network_missing.py, network_hints.py, network.py
- Slides: Part 3: Feedfoward Networks
- Exercises: Backpropagation
3rd Week: Replicating a Model
- Code: network.py
- Patterns: tyler_patterns.csv
- Slides: Part 4: Replicating a Model
- Exercises: Replication of Tyler et al. (2000)
- Tyler, L. K., Moss, H. E., Durrant-Peatfield, M. R., & Levy, J. P. (2000). Conceptual structure and the structure of concepts: A distributed account of category-specific deficits. Brain and Language, 75(2), 195-231.
4th Week: Writing up Experimental Results
- Code: network.py, graph.py
- Example file for errors: errors1000.txt
- Slides: Part 5: Writing the Report
- Exercises: File Input/Output
- Learn Python the Hard Way
- How to Think Like a Computer Scientist: Learning with Python
- Think Python: How to Think Like a Computer Scientist
- Numpy Tutorial
- Matplotlib Examples
- A Primer on Scientific Programming with Python
- Scipy Lecture Notes
- The Glowing Python: This blog has various examples of interesting code to play with and give you ideas for your own projects.
- WildML: Recurrent Neural Networks Tutorial, Part 1 – Introduction to RNNs: This blog also has other Machine Learning tutorials.
- Machine Learning, by The Royal Society
- The Cognitive and Computational Neuroscience of Categorization, Novelty-Detection, and the Neural Representation of Similarity, by Mark Gluck
- Machine Learning, by Andrew Ng
- Neural Networks for Machine Learning, by Geoffrey Hinton
- Introduction to Neural Networks, by Sebastian Seung
How to install Python
This is a little tricky:
Install Python: download from here
Install matplotlib, numpy, and scipy using pip. Specifically you need to download the following from here:
This requires you to be in the Scripts folder of the Python27 installation. And to use the windows command prompt. For me this looks like:
C:\Python27\Scripts>pip install NAME_OF_WHEEL_FILE.whl
For all three of those you need to run a pip command like above.
Install PyGTK: download from here
To check that everything works, open network.py and see if it runs without any errors.
I finally managed to do this on my mac. Use Homebrew to install matplotlib, numpy, scipy, pygtk.
Use your favourite package manager to install matplotlib, numpy, scipy, pygtk.