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An Interactive Machine Learning Toolkit

https://marcelle.dev

Marcelle is still experimental and is currently under active development. Breaking changes are expected.

Marcelle is a modular open source toolkit for programming interactive machine learning applications. Marcelle is built around components embedding computation and interaction that can be composed to form reactive machine learning pipelines and custom user interfaces. This architecture enables rapid prototyping and extension. Marcelle can be used to build interfaces to Python scripts, and it provides flexible data stores to facilitate collaboration between machine learning experts, designers and end users.

See online documentation

Using NPM:

npm install @marcellejs/core --save

Using Yarn:

yarn add @marcellejs/core

See Online Documentation

To build for production:

yarn build # OR npm run build

To build for development (watch mode):

yarn dev # OR npm run dev

To generate the typescript declaration files (useful for the rollup example), run yarn build:types in production, or yarn dev:types in development.

Download VSCode and install the following extensions:

• Svelte for VS Code
• ESLint
• Prettier - Code formatter
• Tailwind CSS IntelliSense

Marcelle is a research project led by Jules Françoise (CNRS researcher at LISN) and Baptiste Caramiaux (CNRS researcher at ISIR).

This research was supported by the ELEMENT project (ANR-18-CE33-0002) from the French National Research Agency.

• Jules Françoise (CNRS researcher at LISN)
• Baptiste Caramiaux (CNRS researcher at ISIR).
• Téo Sanchez (PhD Student at LISN)

Please cite the following publication when refering to Marcelle in academic publications:

Jules Françoise, Baptiste Caramiaux, Téo Sanchez. Marcelle: Composing Interactive Machine Learning Workflows and Interfaces. Annual ACM Symposium on User Interface Software and Technology (UIST ’21), Oct 2021, Virtual. DOI: 10.1145/3472749.3474734.
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