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A Python library for space AI benchmarking

Project description

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Python Version from PEP 621 TOML pre-commit Checked with mypy

Import sorted with isort IMport cleaned with pycln Code style: black Doc style: docformatter

SpaceAI is a comprehensive library designed for space mission data analysis and machine learning model benchmarking. It provides tools for data preprocessing, model training, and evaluation, specifically tailored for space-related datasets. The library includes implementations of various machine learning models, such as ESNs (Echo State Networks) and LSTMs (Long Short-Term Memory networks), and offers a range of utilities to facilitate the development and testing of these models. With SpaceAI, researchers and engineers can streamline their workflow and focus on deriving insights from space mission data.

Here's the link to the documentation: https://space-ai.readthedocs.io/en/latest/

Installation

To install SpaceAI and all its dependencies, you can run the following commands:

pip install spaceai

Credits

We thank eclypse-org and Jacopo Massa for the structure and the template of the documentation!

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