Basic neural network with julia
In this post I will try to describe building a basic regression model with gradient descent. This forms a very basic prototype of neural network. This by no means is a full fledged neural network, but this makes very fundamental foundation of neural network. Feedforward to calculate the error and back propagation to update the weights and biases from the error function. The code cells can be collected into a script and run as an individual julia script to reproduce everything that is described here in this article. ...