Tiny & Light weight Machine Learning Library
Project description
Bishõgrad
A Bishõ Autograd engine in python along with a lightweight deep neural-network library! (inspired from mircrograd by Andrej Karpathy)
what's Bishõ?
微小 - Bishõ is Japanese word for 'tiny' since my implementation is very tinyyyyy ^_^ compared to PyTorch/Tensorflow
what's Hako?
箱 - Hako is Japanese word for 'box' , here Hako signify the neurons in our network ;D
Installation
[!NOTE] Package is not released on pypi
-
Manually build the wheel file and install it:
- Clone this repo:
git clone https://github.com/AK3847/Bishograd.git cd Bishograd
- Use a python package manager like Rye to build the wheels:
rye build
- Use
pipto install the package into your virtual env:pip install path/to/the/wheel/file/bishograd-0.1.0-py3-none-any.whl
- Clone this repo:
-
Download the temporary wheel file from here
- Use
pipto install the package into your virtual env:pip install path/to/the/wheel/file/bishograd-0.1.0-py3-none-any.whl
- Use
Example
Wonder how this works? Checkout the examples.
Targets :
- ReLU Activation function
- Add MLP.training() to automate the whole training code
- Add
Sigmoid, LeakyReLU & other activation functions - Add loss functions - categorical loss, mean-square loss etc
Contribution :
This repository is open for contribution! Primary way to contribute is to either raise an issue or a pull request with proper description and code format. You can contribute to any Targets or add new features as well.
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