Since we're on the topic of tutorials to understand neural nets and modern deep learning, I will throw in Michael Nielsen's excellently written free online "book" on neural nets. It's really a set of 6 long posts that gets you from 0 to understanding all of the fundamentals with almost no prerequisite math needed.
Using clear and easy to understand language, Michael explains neural nets, the backprop algorithm, challenges in training these models, some commonly used modern building blocks and more:
This book opened my eyes to the power of textbooks written in such easy to understand, clear style. Bet it took repeated revisions, incorporating feedback from others and hours of work but such writing is a huge value add to the world.
Using clear and easy to understand language, Michael explains neural nets, the backprop algorithm, challenges in training these models, some commonly used modern building blocks and more:
http://neuralnetworksanddeeplearning.com/
This book opened my eyes to the power of textbooks written in such easy to understand, clear style. Bet it took repeated revisions, incorporating feedback from others and hours of work but such writing is a huge value add to the world.