These are some basic machine learning algorithms I implemented for school homework or for experiment.
Hope this can help beginners who are interested in R/Python programming and ML.
Note: All code are NOT optimized!

Current Models:

• Colaborative Filtering (R)
• Matrix Factorization (java)
• linear regression (python)
• logistic regression (python, R)
• Naive Bayes (python)
• Add SVM with SMO method (pyhton)
• Gaussian mixture model (python, PyMC)

TODO:

• kernel for SVM
• GLMNET for linear