This is not a Machine Learning framework.
This is an implementation of fundamental mathematics of ML (specifically, Neural Networks) just for fun.
$ python main.py
main.py
- training experiment: architecture and hyperparametersactivation.py
- activation functions and their derivativesalgebra.py
- vector and matrix operationsdata.csv
- Iris dataset for training/evaluationdata.py
- data loading, shuffling, normalisationmetrics.py
- evaluation metrics and loss functionspropagation.py
- backpropagation algorithmtrain.py
- parameter initialisation and model training
- Train/evaluation data split
- Stochastic gradient descent
- More activation functions
- Softmax
- Regularisation
- Refactor all the things
- Optimise all the things