Making the switch from traditional development to data science took some adjusting. I knew little about tensors, regression, epochs, hyperparameters, or that a CNN wasn’t just a news channel on my TV.

AI is all around us and interest in machine learning, computer vision, and deep learning are growing at a rapid rate. For the past 20 + years I’ve built websites for music artists, enterprise backends, prototypes for car dashboards, and even large touch screen installations. However, I wish I knew these things before I switch to deep learning.

In this talk, we’ll go through some of the most common pitfalls developer make when diving into the machine learning deep end.