Course-Machine-Learning-for-Physics-and-Astronomy

In this course we learned the theory and the application of multiple basic machine learning algorithms like: linear regression, gaussian process regression, logistic regression and clustering. We also discussed deep learning and we made classification and regression networks and made networks that could classify images. We made these networks with pytorch. I have added the homework exercises to show. what we did. An important difference between this course and the data mining course that I also followed is that in this course we made the ML algorithms from scratch with libraries like numpy instead of using more advanced libraries as SKlearn