Project folder for all my Jupyter Notebooks and NBA data.

Predicting NBA MVPs using machine learning

NBA players clustering and Points prediction

Jupyter notebook that outlines the process of creating a machine learning predictive model. Predicts the peak "Wins Shared" by the current draft prospects based on numerous features such as college stats, projected draft pick, physical profile and age. I try out multiple models and pick the best performing one for the data from my judgement.

A notebook of building a logistic classification model, random forest classifier, and a support vector machine (SVM) classifier - all using Scikit-Learn!

Jupyter Notebook that scrapes NBA player salary data from espn.com, injects that data into an existing dataset (one owned by TrueHoop CEO and CoFounder Henry Abbott), and exports the resulting augmented dataset to a .csv file.

This is the notebook of our final project for CMSC320: Introduction to Data Science. In this project, we explore Hall of Famers in the NBA.