Welcome to itwinai’s documentation!
itwinai is a framework for advanced AI/ML workflows in Digital Twins (DTs).
This platform is intended to support general-purpose MLOps for Digital Twin use cases in the interTwin project.
Platform for machine learning workflows in digital twins
The goal of this platform is to provide ML researchers with an easy-to-use endpoint to manage general-purpose ML workflows, with limited engineering overhead, while providing state-of-the-art MLOps best practices.
How to read the docs
To effectively utilize the itwinai framework documentation, start by exploring the “Getting started” section.
This section is crucial for understanding the basics, setting up the framework, including detailed instructions for
different types of installations such as User Installation either on HPC or on your laptop and Developer Installation.
For a deeper understanding of the toolkit’s core functionalities, refer to the “How It Works” section, which covers
key concepts addressed by itwinai.
The “Scientific Use Cases” section provides practical examples and interTwin project use cases’ scenarios where itwinai
has been applied, offering valuable insights into real-world applications.
To further enhance your skills, explore the “Tutorials” section, which includes comprehensive
guides on Distributed ML training and ML workflow tutorials. Lastly, the “Python API Reference” section is an essential
resource for detailed information on the framework’s API, helping you to implement specific features and functions in your projects.
By following these sections systematically, you can maximize your understanding and effective use of the itwinai framework.
itwinai documentation also offers different versions, such as the ‘latest’, ‘stable’, and ‘v0.2.1’.
The ‘latest’ version includes the most recent updates and features reflecting main branch developments,
while the ‘stable’ version tracks the most recent project release based on semantic tagging and is recommended for production
use due to its reliability (learn more).