http://iamtrask.github.io/2015/07/12/basic-python-network/
This shows a very simple neural network written in 11 lines of python! (it uses numpy too).
It is really great, but for simplicity it doesn't use biases and is very basic...(Not including bias terms means that the net activation of a neuron will never be more than 0.5 [using a sigmoid neuron] in the case that all inputs to that neuron are 0...It's not a huge barrier to learning, but it's also just not the norm.)
He goes through each line of the code and explains it.
It's really hard to get your head around how lines 8 and 9 work...but he explains a bit later on.
http://neuralnetworksanddeeplearning.com/
This resource is a bit long for the casual reader, but it is well worth it...He derives the weight updates and accompanies everything with an explanation and explanatory code!
https://www.youtube.com/channel/UCWN3xxRkmTPmbKwht9FuE5A/playlists
He delivers high quality Neural Network resources/walkthroughs like a G.
https://www.reddit.com/r/MachineLearning/
(A great place to learn about machine learning...if you feel you have simple questions which shouldn't muddle the discussion there, it's preferred you ask them here: https://www.reddit.com/r/learnmachinelearning/)
https://github.com/josephmisiti/awesome-machine-learning