If you just pick up a math book, you'll learn lots of stuff that you don't need to know. That's fine, but it strikes me as a good way to avoid actually doing an

If you just pick up a math book, you'll learn lots of stuff that you don't need to know. That's fine, but it strikes me as a good way to avoid actually doing anything and gaining practical experience. If you hit a wall in practice because you don't understand the math, you'll usually have enough of an idea of the problem to ask more intelligent questions about what kind of math you need. That will, incidentally, help you understand the math better because you're coming to it out of an actual need rather than just seeing it mixed into a bunch of chapters. Unless you're going to write a machine learning framework or be a researcher, the required math isn't too bad and it sounds like you might have enough of a background already. So don't be afraid to dive into something practical (like a kaggle competition). FWIW this is a really good blog for insight into the math and intuition behind deep learning: http://colah.github.io/ http://colah.github.io/ (i'm not sure if it's quite what you're looking for though)