This was the first time I actually grokked backpropagation, just the first video alone is more lucid and valuable than any other resource about machine learning I had seen before, in fact it's so well explained that i managed to implement the library almost completely from memory after watching it - I cannot recommend it highly enough, especially for programmers without a math background!

The only aspect I could see being non-ideal for some is that it uses some Python-specific cleverness/advanced syntax and semantics (__call__(), list comprehensions with two for's, **kwargs, __add__, __repr__, subclasses, (nested) functions as variables etc.), but if you are familiar with these it might seem more compact and elegant as well.