A repository for a variety of Machine Learning problems.
The DSBC team has spent years developing tools and training materials for Applied Math and Data Science. In this project you will find the following tools.
- "Notes on ..." these are cheet sheets on various topics of Machine Learning, e.g. algebra, calculus, probability theory, etc.
- A textbook "Math Refresher fo ML" for those who aspire to understand the math fundamentals of Machine Learning.
- Lecture slide for the "Math Refresher fo ML".
- A short book or tuitorial on Neural Nets and Machine Learning.
- Software written in both Python and Matlab with many packages included for Data Scientists, e.g. Linear Programming, Monte Carlo, Neural Networks, LSTM, etc.
We use TortiseSVN for versioning. For the versions available, see the tags on this repository.
This project is licensed under the MIT License - see the LICENSE.md file for details.