September 05, 2015
Here I'm going to revisit backpropagation theory by thinking about neural networks as computational graphs upon which we can easily visualize the chain rule to compute partial derivatives.
August 10, 2015
A beginner tutorial for an even simpler recurrent neural network implementation in Julia.
August 05, 2015
A beginner tutorial on building a simple (Elman) recurrent neural network in Python. We'll build an RNN than can compute XOR on sequential data and another that can predict the next character in a sequence.
July 31, 2015
A beginner tutorial to understand the theoretical and implementation details of gradient descent by backpropagation using Python.
July 15, 2015
Beginner tutorial on writing a genetic algorithm to train a simple 2-layer feed-forward neural network. (Ok, I admit it, the "15 lines" is a gimmick)