Hello! This repository is a work in progress; soon to be a somewhat interactive Machine Learning educational resource. Hopefully this will be a helpful resource for people beginning to learn Machine Learning/ AI/ Data Science concepts, or anyone who just wants to review. I know that when I was first learning about Machine Learning etc., I was pretty lost in terminology and would've loved a single resource for all my questions. There have been some great resources that I have found very helpful along the way, and I have been lucky enough to also have some experiences that have furthered my Machine Learning knowledge - so I figured compiling what I've learned into one place may be helpful, not just for me, but for others too.
My name is Tate Keller, I'm a Master's student at Cornell Tech studying Information Science, with a concentration in Health Technology. Previously, I studied at Case Western Reserve University, where I majored in Systems Biology and minored in Computer Science.
Generally, I have a passion for Math and Statistics, and its applications in tech today. Specifically, I think its applications in BioTech (specifically bioinformatics/genomics) and Transportation Tech (autonomous vehicles etc) are super exciting. I'm actively seeking a full time job in either space - specifically looking for Machine Learning Engineering / Data Science positions.
You may want to have a basic background in Math or Statistics, but I will try my best to explain things at a very simple level to make it understandable to all audiences. Additionally, as of now, I plan to make this entirely in Python. Perhaps there will be some R if I go over informatics type topics.. but I'm not there yet. Nonetheless, a basic understanding of programming will be helpful, but I will comment and annotate everything to the best of my ability.
I set the language of each jupyter notebook to correspond to the primary programming language used in the notebook, since jupyter notebook can be vague (Markdown? Python? R? Julia?).