![Code Quality Status](https://github.com/schmidtbri/ml-base/actions/workflows/test.yml/badge.svg)
[![License](https://img.shields.io/badge/license-BSD--3--Clause-green)](https://opensource.org/licenses/BSD-3-Clause)
[![PyPi](https://img.shields.io/badge/pypi-v0.2.2-green)](https://pypi.org/project/ml-base/)
# ml-base
**ml-base** is a package that provides base classes and utilities that are useful for deploying machine learning models.
## Installation
The easiest way to install ml-base is using pip
```bash
pip install ml-base
```
## Usage
There are several examples of how to use the ml-base framework in the
[documentation](https://schmidtbri.github.io/ml-base/).
## Development
First, download the source code with this command:
```bash
git clone https://github.com/schmidtbri/ml-base
```
Then create a virtual environment and activate it:
```bash
# go into the project directory
cd ml-base
make venv
source venv/bin/activate
```
Install the dependencies:
```bash
make dependencies
```
## Testing
To run the unit test suite execute these commands:
```bash
# first install the test dependencies
make test-dependencies
# run the test suite
make test
# clean up the unit tests
make clean-test
```
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