These are notebooks I created to teach incoming freshman/undergraduates machine learning for performing research with the Compact Muon Solenoid experiment at Purdue University
Some of this has been inspired from: https://github.com/Atcold/pytorch-Deep-Learning, Thank you Alfredo for this amazing resource and being one of the first people to truly introduce me to machine learning. However, a lot of the mathematics and details in this course I felt were assumed. Since this is for freshman I decided to create my own resource to try and build the foundations of machine learning from the ground up in a nice and conversational approach through Jupyter notebooks. Hopefully others will find these useful.
Lab 0 has some information specific to students taking the research class at Purdue, but may be a nice Bash introduction for some people. Lab 1 is mostly Alfredo's PyTorch notebook with some added explanations here and there to try and bridge the knowledge gap.
Lab x is the spiral classifier adapted from Alfredo's PyTorch minicouse. However, I have greatly expanded upon this as I think this is a very nice, simple example that is non-trivial to get very high generalization with a deep neural network and therefore excellent for educating newcomers to machine learning on the limitations and the challenges to using deep learning effectively.