AI-Blocks is a visual, WYSIWYG editor that lets anyone create machine learning models by dragging functional blocks onto a scene โ no code required to start. Blocks carry scripts for data, layers and training logic; the assembled model can run directly inside the editor or be exported as a standalone TensorFlow script. It is an open-source project on GitHub with around 1,900 stars, dating from 2023.
The idea borrows from game-engine editors: a canvas of draggable objects, each representing a piece of a neural network pipeline, whose parameters are edited through inspectors rather than code. Python script variables are parsed and surfaced as editable fields, so advanced users can still customize block behaviour while beginners stay in the visual layer. AI-Blocks targets education and rapid experimentation โ sketch a model, run it, see results, then export the generated TensorFlow code when you are ready to move to a conventional workflow.
Free. AI-Blocks is open source and free to download and use.
The block library covers the usual building pieces of a small neural network workflow โ data inputs, dense and convolutional style processing blocks, activation and output blocks โ and connections between blocks define the data flow of the model. Because blocks expose their underlying Python, a project can start fully visual and gradually become code as the user’s skills grow, and finished scenes double as shareable teaching artifacts that others can open, run and remix.
Students, educators and curious beginners who want to understand and build neural networks visually before (or instead of) writing framework code.