This repository contains various machine learning/data science projects that I’ve done. A brief summary of each:

• Fundamental Analysis: Applies machine learning to stocks in the Wilshire 5000 index to predict whether a given stock price will increase or decrease over the coming year. Uses fundamental analysis as features.
• Lyric Analysis: Analyzes the broad lyrical trends of four different genres - rap, rock, country, EDM - and trains an LSTM network to generate new lyrics with similar properties as the genre upon which it was trained (blog post in prep).
• Performance_After_Payday: Determines whether baseball players who get huge salary increases tend to perform better or worse in the following year.
• Stock_Correlation: Performs stock correlations and unsupervised stock clustering for different financial sectors.

Blog posts on these projects can be found at https://silburt.github.io/blog.html