Fenn
Fiscal Host: Open Source Collective
Friendly Environment for Neural Networks (fenn) is a simple framework that automates machine learning and deep learning workflows
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About
Fenn is an open-source framework designed to simplify AI workflows. It is intended for students, researchers, and developers who want a structured way to design, test, and manage AI-based solutions. The project originated from my experience as a research fellow at the University of Parma, Italy.
Beyond academic use, the framework can also support companies during the design and prototyping phase of AI-driven solutions.
Although the project is relatively new, it already has a growing community. We actively welcome new contributors by maintaining well-documented issues. We also run an active Discord community where newcomers can ask questions, discuss ideas, and receive support from other users and contributors.
The project has also been recognized by the open-source community and included in the good-first-issue list and in the awesome-data-analysis list.
I am currently raising funds to support the sustainability and future development of the project. Contributions will help cover essential infrastructure costs such as website hosting and domain maintenance.
Funding will also support several planned improvements, including:
Beyond academic use, the framework can also support companies during the design and prototyping phase of AI-driven solutions.
Although the project is relatively new, it already has a growing community. We actively welcome new contributors by maintaining well-documented issues. We also run an active Discord community where newcomers can ask questions, discuss ideas, and receive support from other users and contributors.
The project has also been recognized by the open-source community and included in the good-first-issue list and in the awesome-data-analysis list.
I am currently raising funds to support the sustainability and future development of the project. Contributions will help cover essential infrastructure costs such as website hosting and domain maintenance.
Funding will also support several planned improvements, including:
- A dedicated platform where users can register, publish, and download built-in templates. At the moment this functionality relies on a GitHub repository, which is difficult to maintain and document properly.
- A self-hosted solution for tracking experiments. Currently users rely on external tools, but the goal is to provide an integrated system directly within the framework.
Supporting the project helps maintain the infrastructure, promote the framework through outreach and visibility efforts, and enables the development of tools that make AI experimentation more accessible, organized, and reproducible.
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