I watched a great video on Tensorflow (link below). It mostly introduces very basic deep learning concepts, but there are a few key moments in the 2 hour+ video

I watched a great video on Tensorflow (link below). It mostly introduces very basic deep learning concepts, but there are a few key moments in the 2 hour+ video, where he explains what to do if something goes wrong. It's definitely not a "science", but with enough experience in deep learning, you can intuit what's going on inside the black box, and there are best practices on what to try next. For example, he goes through a few examples where a neural net has too many weights, or too little data or improperly connected nodes. All three result in problems, but the problems exhibit themselves in slightly different ways and with expertise you can start identifying them. https://www.youtube.com/watch?v=vq2nnJ4g6N0 https://www.youtube.com/watch?v=vq2nnJ4g6N0