This repo will provide useful tookits for machine learning. Mainly including the following four parts:
- For_10601
10601 is one of the machine learning courses in CMU,I am right now taking this course. Using any external packages other than numpy is forbiddened in this course. So we need to build the wheel by ourselves. so this dictionary will provide basic toolkits used in the homeworks (they may already be developed and can be used by import packages like pandas). - Algorithm
In this part, there will be Algorithms for different machine learning models. And may also include the brief explanation of math used in the model. - Toolbox
I will collect useful toolkits that may be used in machine learning. For instance: data cleaning , featurization, ML-DFT autoworkflow, and some cheatsheet of useful packages (like pandas,pymatgen,sk-learn e.) - Examples
This part will give you examples in the real world or real research. (But i guess the cases in Materials Science would be in majority,cause i am a MSE student) There would be tutorials and raw databases, you can try to train a machine learning model by yourself, Sounds amazing, doesn't it?