Awesome

Vectorized monolayer perceptron

This is a simple perceptron made with Simple Linear Algebra for C# , is a neural network that can calcule Xor Xnor And Or via Stochastic gradient descent backpropagation with Sigmoid and Relu as Activation function.

There is a lot to improve, like csv read, gpu implementation, regularization, but is functional.

How use it

Just go to the project and open Program.cs and run it, you can change the dataset changing X and Y variables

How use Relu

0. Change all sigmoid function, for relu function
1. a3 must have no Nonlinear function Matrix a3 = z3;
2. because of that Delta3 has not derivated Matrix Delta3 = a3Error * 1;
3. The learning rate must be smaller, like 0.001

Where can i learn more

• On my Youtube channel (spanish) are a lot of information about Machine learning and Neural networks
• https://www.youtube.com/channel/UCS_iMeH0P0nsIDPvBaJckOw
• You can also look at the generalized Example of This
• https://github.com/HectorPulido/Vectorized-multilayer-neural-network
• Or Look at a Non Vectorized multilayer perceptronExample
• https://github.com/HectorPulido/Multi-layer-perceptron

Patreon

Please consider Support on Patreon https://www.patreon.com/HectorPulido