I hope to explore how to use AI in the field of microfinance to help reduce income inequality. Microfinance has greatly helped decrease rural poverty rates in Bangladesh. The leader of this effort won the Nobel Peace Prize for his work. These micro-loans give opportunity to those who are not otherwise able to obtain financing for their entrepreneurial ideas. This can be applied in the U.S. too, in places where the population cannot otherwise obtain loans to start small businesses and climb their way out of poverty. It can be very difficult to start from rock bottom in the US, especially for those without access to resources. If people could obtain small loans and start small businesses, they could work their way out of poverty. The microloans have to be viable for banks as well. The problem I’d like to explore is whether AI/ML can be used to determine how to deploy microloans efficiently to address income inequality in the U.S.

This project observes how various machine learning models, once tuned, can further be combined to create a complex model that uses NFL data from the past 18 years to predict the outcomes of matchups between any two competing teams.

It is important to have a reliable application that can aid users of betting and fantasy football in which players they should put bet on, or choose for their fantasy teams. My motivation behind this project was to create something that could further betting and fantasy football, and even increase traction.