Some of the other projects I worked on includes a django project where with a small team of people we would build a functional django website and tests for that website. I have also build numerous small projects like a calculator and other similar projects using python.

Currently me and another friend are working on another project. This project is based around the concept of Arbitrage betting. This is the process of finding favourable bets, usually on sports events, where your chance of losing money is 0% and earning money is nonzero. This is usually done by gathering data from multiple different book keepers and finding opportunities by betting against your self. As part of this project we will be automating the bet finding process. We are writing a program that will gather all the data we want and compare to see if an arbitrage opportunity exists.

Another project that I am taking on alone is "Intrusion detection system for IOT networks using federated learning". As part of this project I will be learning how to do ML and FL. I will also be producing a 40 page dissertation at the end of my project. Federated Learning is version of ML. Instead of gathering all the data in a central server using federated learning we keep the data at the edge of the network preserving privacy. We then train local models using local data at client devices. Then using privacy preserving aggregation techniques we gather client model weights. Averaging these models to get a global model which is then distributed around. This method preserves the privacy of the users involved and reduces compute requirements on the central server.