This group of ipnyb files are my MLP codings without(or mostly without) prebuilt machine learning libraries such as pytorch, scikit(other than utilizing the datasets), etc...

If you wonder why I didn't use those elegant faster, and easier to use libraries that others have already created, I just wanted to see if I understood how these basic ML parts work. So I tried avoiding libraries built for ML, and made my own functions from numpy.

Basic structure of these codes come from Datascience School's Deep Learning Advanced Course and Yonsei University's Machine Learning Courses. Assignments from these courses gave the basic layout of codes, and the students had to fill in the functional parts.