This is a folder filled with Jupyter notebooks of common machine learning techniques with examples. The table of contents are down below:
- 1D Classfication
- Regression and Overfitting
- Multiple dimensional Classfication/Regression(Multivariate Gaussian)
- Kernal density estimates
- Mixture models?
- Clustering (Meanshift,Kmean)
- Dimensionality Reduction (PCA,LDA,)
- Nerual networks
You can view my notebooks in the machine learning notebook folder. You can view the Python notebook by either opening it up in Github, but I highly recommend openning it up in https://nbviewer.jupyter.org/ instead. Then you can interactive with the notebooks.
If you want to run the notebooks for some reason yourself you can use the docker container docker-compose build docker-compose up