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