This code is a general repository of projects I have worked on.

Fraud Prevention is a workup of a simple ecommerce sample data of fraudulent activity that successful predicts future fraud with either a linear regression model or random forest.

Employee Analysis has an example dataset of statistics on various companies across different departments and statistics on their benefits and retention rates.

There is also an overview of classification techniques on the MNIST dataset and a best fit model that classifies the dataset with visual noise and rotational noise.