I first looked into machine learning and understanding some of the basics around training models, understanding core concepts such as what a feature is a few years ago. I then dropped it because at the time I did not have a clearly defined use case in my work and I lacked time, with too many projects on at the same time, personal and professional.

I now have a use case, but it’s been years since I looked at ML, it was around the time Tensorflow was released. At the same time now there’s a lot of hype around it again like there was a few years ago because of the work by OpenAI and possibly even due to lull in excitement with blockchain and crypto. That makes this space even harder to navigate.

What’s a good place for an experienced engineer to start now? Any good books or references for understanding concepts on the last research? Understanding the concepts is what I’m primarily interested in for now, then I hope I can figure out where to go from there on my own tech stack wise. I already have a dataset to use for training and and understanding of the type of analysis and questions that I want answered, I’m unclear on the fundamental concepts and approach. Basically when I was kid I wondered how a video game was made. Now I know how to make one from the ground up, from graphics rendering, physics engines, gameplay programming and the rest. I’m at a place now with AI where I’ve got my dataset (that changes and grows over time) and analysis and questions I want answered but I need to understand how to get started.