Find a problem to work on in a domain you find interesting. By reading published papers and trying to attack the problem, you&#x27;ll be forced to pick up a lot of other knowledge not commonly discussed like: feature extraction and selection, dimensionality reduction, dealing with sparsity, common metrics for that problem, recent work, etc.<p>I was forced to learn a massive amount in a short period of time for work, but I&#x27;d previously watched Andrew Ng&#x27;s lectures, as well as majored in Math&#x2F;CS. I can also generally recommend Hinton&#x27;s NN lectures, Socher&#x27;s Deep learning for NLP, Andrew Ng&#x27;s Machine Learning, and a few books.