front matter
Like many data scientists and machine learning engineers out there, most of my professional training and education came from real-world experiences, rather than classical education. I got all my degrees from Johns Hopkins in theoretical mathematics and never once learned about regressions and classification models. Once I received my master’s degree, I decided to make the switch from pursuing my PhD to going into startups in Silicon Valley and teaching myself the basics of ML and AI.
I used free online resources and read reference books to begin my data science education and started a company focusing on creating enterprise AIs for large corporations. Nearly all of the material I picked up focused on the types of models and algorithms used to model data and make predictions. I used books to learn the theory and read online posts on sites like Medium to see how people would apply that theory to real-life applications.