In a seris of previous posts we, described how to make a [fully functional Neural Network][fnn] in julia. Lets create a package so that we can import the neural network in julia as a regular package …
After a series of [previous posts][activation-func] we hav learned the key steps of making a Machine Learning: 1. [Gradient Descent][basicnn] 2. [Back Propagation][backprop] 3. [Adding Multiple …
As we saw in [previous post][multinode] addition of any number of layers and any number of nodes will only be able to model a linear functions. If we want our network to also be able to learn non …
In the previous two posts we have already seen how to construct a single neuron neural network with or without hidden layer. If we want to input multidimensional input and get multidimensional output …
## Setup Similar to [last post](/posts/2022/05/basic-neural-network-with-julia/), where we made a basic neural network with just one neuron and no hidden layer, we will build a two neuron and a …
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, …