GliaML - Python Machine Learning Library
Project description
GliaML is simple, yet powerful machine learning library written in Python.
Currently, it allows a user to easily create a multi-layer perceptron neural network with the following features:
Allow backpropagation with the sigmoid, tanh, and ReLU activation functions.
Allow normalisation of a classifier with the softmax function.
Allow learning rate hyperparameter functionality (including biases)
See example.py for usage.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
gliaml-0.0.2.tar.gz
(7.9 kB
view hashes)
Built Distribution
gliaml-0.0.2-py3-none-any.whl
(13.3 kB
view hashes)
