CharityML is a fictitious charity organizationy that was established to provide financial support for people eager to learn machine learning. CharityML determined that every donation they received came from someone that was making more than $50,000 annually. To expand their potential donor base, CharityML has decided to send letters to residents of California, but to only those most likely to donate to the charity.

• This project helps build an algorithm to best identify potential donors and reduce the overhead cost of sending mail. It will evaluate and optimize several different supervised learners to determine which algorithm will provide the highest donation yield while also reducing the total number of letters being sent.