julius/prototorch
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Update readme

Browse Source
This commit is contained in:
Jensun Ravichandran 2020-09-24 11:54:32 +02:00
parent a8a99f6971
commit 9b5bccc39d
1 changed files with 21 additions and 20 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

41
README.md
View File

@ -1,7 +1,6 @@
# ProtoTorch
# ProtoTorch: Prototype Learning in PyTorch
ProtoTorch is a PyTorch-based Python toolbox for bleeding-edge research in
prototype-based machine learning algorithms.
![ProtoTorch Logo](https://prototorch.readthedocs.io/en/latest/_static/horizontal-lockup.png)
[![Build Status](https://travis-ci.org/si-cim/prototorch.svg?branch=master)](https://travis-ci.org/si-cim/prototorch)
![tests](https://github.com/si-cim/prototorch/workflows/tests/badge.svg)
@ -12,18 +11,14 @@ prototype-based machine learning algorithms.
![PyPI - Downloads](https://img.shields.io/pypi/dm/prototorch?color=blue)
[![GitHub license](https://img.shields.io/github/license/si-cim/prototorch)](https://github.com/si-cim/prototorch/blob/master/LICENSE)
*Tensorflow users, see:* [ProtoFlow](https://github.com/si-cim/protoflow)
## Description
This is a Python toolbox brewed at the Mittweida University of Applied Sciences
in Germany for bleeding-edge research in Learning Vector Quantization (LVQ)
and potentially other prototype-based methods. Although, there are
other (perhaps more extensive) LVQ toolboxes available out there, the focus of
ProtoTorch is ease-of-use, extensibility and speed.
Many popular prototype-based Machine Learning (ML) algorithms like K-Nearest
Neighbors (KNN), Generalized Learning Vector Quantization (GLVQ) and Generalized
Matrix Learning Vector Quantization (GMLVQ) are implemented using the "nn" API
provided by PyTorch.
in Germany for bleeding-edge research in Prototype-based Machine Learning
methods and other interpretable models. The focus of ProtoTorch is ease-of-use,
extensibility and speed.
## Installation
@ -44,25 +39,31 @@ cd prototorch
pip install -e .
```
## Documentation
The documentation is available at <https://prototorch.readthedocs.io/en/latest/>
## Usage
### For researchers
ProtoTorch is modular. It is very easy to use the modular pieces provided by
ProtoTorch, like the layers, losses, callbacks and metrics to build your own
prototype-based(instance-based) models. These pieces blend-in seamlessly with
numpy and PyTorch to allow you mix and match the modules from ProtoTorch with
other PyTorch modules.
Keras allowing you to mix and match the modules from ProtoFlow with other
modules in `torch.nn`.
### For engineers
ProtoTorch comes prepackaged with many popular Learning Vector Quantization
(LVQ)-like algorithms in a convenient API. If you would simply like to be able
to use those algorithms to train large ML models on a GPU, ProtoTorch lets you
do this without requiring a black-belt in high-performance Tensor computing.
ProtoTorch comes prepackaged with many popular LVQ algorithms in a convenient
API, with more algorithms and techniques coming soon. If you would simply like
to be able to use those algorithms to train large ML models on a GPU, ProtoTorch
lets you do this without requiring a black-belt in high-performance Tensor
computation.
## Bibtex
If you would like to cite the package, please use this:
```bibtex
@misc{Ravichandran2020,
@misc{Ravichandran2020b,
author = {Ravichandran, J},
title = {ProtoTorch},
year = {2020},