Introducing Machine learning algorithms to calculate DMFT+DFT problems.

1) There is a paradigm shift in the group towards using machine learning algorithms to solve DMFT problems. This is being done to streamline the process one is required to go through to solve problems. This can be achieved by introducing a set of known solutions as training data

2) The monte carlo simulation of the J1J2 model is being used as a means to familarise myself with the physics and code that explains the frustrated ising model.