Able to use music21, keras CNN & RNNS to help convert midi files into notes, then integers to feed to RNN & CNN neural networks of deepwave and LSTM architectures .  Able to generate very simple notes/midi files.  You can see the work here!

Predicted whether a borrower will default using various classification algorithms.

Used various classification algorithms, using Python, Pandas, Scikit-Learn, achieving 95% AUC score. Check out credit risk analysis!

This project involves data processing using statistical techniques to deal with outliers, imputation techniques to deal with nulls.  Then apply linear regression models through Scikit_Learn, along with standard scaler, polynomial features, regularization through ridge and lasso in order to construct the best model that can predict the price of a home in Ames, Iowa.  Check out the repo!

Collected data using Beautiful Soup, Rest API in order to obtain about 20,000 reddit posts.  Used NLP techniques to vectorize the posts to then help train a classifier on whether a post came from the coffee subreddit or the tea subreddit.  Also able to get insights on how these different users speak about their beverage of choice! You can find out more in its repository.