Machine Learning

This is a folder filled with Jupyter notebooks of common machine learning techniques with examples. The table of contents are down below:

Table of contents

• 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

How to view

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.

For Docker

If you want to run the notebooks for some reason yourself you can use the docker container docker-compose build docker-compose up