newberry-metrics 0.0.20

A model evaluation tool

Newberry Metrics

A Python package for model evaluation that provides tools and utilities to assess machine learning model performance.

Description

Newberry Metrics is a lightweight and efficient tool designed to help data scientists and machine learning engineers evaluate their models. It provides a suite of metrics and evaluation tools to assess model performance.

Installation

You can install the package using pip:

pip install newberry_metrics

Requirements

• Python >= 3.10

Features

• Model evaluation tools
• Performance metrics calculation
• Easy-to-use interface

Usage

from newberry_metrics import cost

# Example usage will be added here

Development

To set up the development environment:

1. Clone the repository

git clone https://github.com/SatyaTheG/newberry_metrics.git
cd newberry_metrics

2. Create and activate a virtual environment

python -m venv .venv
source .venv/bin/activate  # On Windows, use: .venv\Scripts\activate

3. Install development dependencies

pip install -e ".[dev]"

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

• Satya - SatyaTheG
• Email: [e-mail]

Version

Current version: 0.0.10

Project Status

This project is under active development. Features and documentation will be added regularly.