The code is divided in two important parts:
- In the main.py file a classification dataset was created by gaussian quantiles for two classes.
- In the neuralNetwork.py the architecture of a neural network with a hidden layer was created using only mathematical resources with the help of the library numpy.
The neural network has some characteristics:
- Training and validation functions
- Forward function
- Back Propagation function (for training)
- Gradient descent function (for training)
- Random parameters initialization
- Hyperbolic tangent activation function
- Mean Square Error (MSE) loss function
- All the hyperparameters are worked in dictionaries
Made by @yepedraza