Blohm Lab Wiki

General Computational Neuroscience

• ELSC Youtube Channel Contains archived computational neuroscience seminars and lectures, including Dayan, Abbot, Pouget..., as well as physiology resources.
• Coursera Computational Neuroscience With instructors Rajesh Rao and Adrienne Fairhall.
• Reza Shadmehr lectures on motor control & learning

Machine Learning

Books

• Tom Mitchell's book
• Smola & Vishwanathan's book
• Daume's book
• Murphy's book
• Shalev-Shwartz & Ben-David's book
• Nilsson's book
• Harrington's book
• Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book
• Hastie, Tibshirani, and Friedman's book; also James, Witten, Hastie, and Tibshirani's book, which has less focus on mathematical foundations and more on applications (in R).

= Online Resources

• ML course by Stanford computer scientist Andrew Ng (requires Coursera signup --> free enrollment)
• Andrew Ng ML course exercises for Python
• Markov Chains explained visually
• Mo Chen's toolbox for all the methods discussed in the book: Pattern Recognition and Machine Learning by C. Bishop
• arXiv Sanity Preserver, an interface to the machine learning section of arXiv; lists recent papers most discussed in social media, and gives similar paper recommendations.

Journal Club Tutorials

See Journal Club#Tutorials.

General Math

• Matrix cookbook
• Image filtering, edge detection, etc. (Computer vision)
• Hough transform tutorial (Computer vision)
• Introductory tutorial on Wavelet transforms
• Imaging Brain Function with EEG: Advanced Temporal and Spatial Analysis of EEG Signals (Book by Walter J. Freeman)
• Bayesian Cognitive Modeling: A Practical Course

MATLAB

• Moler's tutorials
• Scott Murdison's compilation
• Jerry Jeyachandra's Curve Fitting Tutorial
  • Curve Fitting Scripts

Statistics

• Rice University online Stats book
• Markov Chain Monte Carlo in practice - book
• Bootstrap methods & significance estimation
• how to do repeated measures ANOVA in Matlab (by Parisa)
• Ten Simple Rules for Effective Statistical Practice
• Testing Hypotheses About Psychometric Functions
• Latin square method for experimental design