Open Source MATLAB Algorithms for Mac

This Matlab package implements machine learning algorithms described in the great textbook: Pattern Recognition and Machine Learning by C. Bishop (PRML). It is written purely in Matlab language. It is self-contained. There is no external dependency. This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry.

MatImage is a Matlab library for image processing and analysis in 2D and 3D. It contains more than 250 fonctions for image enhancement, filtering, analysis, or visualisation, as well as for creating basic test shapes. It is built as a complement of the Mathworks image processing toolbox (IPT). Project is being transfered to GitHub: http://github.com/dlegland/matImage