ML Block is a visual, block-based web application that lets anyone build and experiment machine learning, reinforcement learning and deep learning with a no code solution. Like Scratch, but for AI.
Users drag and drop visual blocks representing ML concepts (layers, datasets, training parameters, etc.) to assemble a complete pipeline. Under the hood, the blocks are translated into a PyTorch or other python AI libraries model that gets trained and evaluated in real time. The interface abstracts away all the code while keeping the logic transparent and educational.
# Clone the repository
git clone git@github.com:PoCInnovation/MLBlock.git
cd ml-block# (TBD)# (TBD)
⚠️ TEMPORAIRE — compte de test du smoke GPU live, à supprimer. Email :smoke-gpu@mlblock.test— mot de passe :d9f8650204fbbef3
You're invited to join this project ! Check out the contributing guide.
If you're interested in how the project is organized at a higher level, please contact the current project manager.
Developers
 Ali BASSIM |
 Chedli OUAZIZ |
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Managers
 Sacha HENNEVEUX |
 Pierre BAUD |
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