This assignment requires students to read a delimited file into a data-frame, apply cursory validations and rename columns if necessary, split the data into testing and training datasets, implement an algorithm using a library such as regression, naive Bayes, clustering, or k-nearest neighbors, apply the model to 20% of the data and provide measures of performance, visualize the model with a simple plot, and write a one-paragraph description of the project and business problem being solved.