Nigerian Airline Frequency Analysis

A summary report of work I did for a Data Analytics II course at SNHU. Fictional company, Austin Air, is looking to enter the international airline industry with a goal of capturing a significant market share of business focused around Nigeria. Analysis will provide a look at the current industry and suggest strategies towards implementing a pilot program for the company to introduce to the market and achieve their goal.

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2018 March Madness Bracket Predictor (part III)

Part three of my attempt to predict NCAA tourney results based on past game data. As cleaning and var creation is out of the way now, this segment will focus on fitting the data to different classifiers in scikit-lelarn and tweaking parameters to determine a classification model with the best prediction power.

Predicting Enron Fraud

Testing and evaluating numerous machine learning techniques to determine best option for predicting fruad occurances in Enron email dataset. The most efficient predictor ended up being an Adaboost algorithm with 50 n_estimators. This method using decision tree as a 'weak learner' came out with about 85% accuracy, p-value of 39, and an r-squared of around 32. Originally conducted for Udacity Nanodegree project.

Predicting a Country's Happiness

A look at the world happiness index and an evaluation of the factors that contribute to the general happiness of a countries population. Variables were primarily focused on economic, political, and elegantarian factors. Originally conducted as a project for my SNHU Applied Stats II class. As it ended at around 30 pages, included is only a subset of the full project.

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