Machine learning application to nuclear physics. A mixture density network (MDN) and random forest algorithms are applied to fit nuclear masses and predict those of nuclei yet to be sinthesized experimentally. The data comes from the AME(2020) and FRDM(2012)
The main files to look at the results are the presentation "Statistical_learning.pdf" and notebook "Projectv5.ipynb".
