This project implements support vector machine and random forest models to create a spam classifier using primarily the url string as features. Because search engines have limited crawl resources, being able to identify a spam url without relying on page content will result in significant resource savings in addition to a reduction of spam for the user. This work implements various features and compares the performance of multiple classifiers in detecting spam

Algorithmic programming contests provide an opportunity to gain insights into coding techiques. let us analyzes contest submissions on Codeforces, a popular competitive programming website where participants solve about 5 to 10 algorithmic problems in a typical contest. We attempt to predict a user’s rank and country based on a single python/C++ source code submission. 

Education is often an expensive gatekeeper to earning potential and, more generally, quality of life as a consequence. As inputs, we will use different variables such as selectivity, tuition, faculty salary, and areas of study to predict mean earnings ten years post enrollment