About

Activeloop provides an optimized format for unstructured data, so users can stream their machine learning datasets while training ML models in PyTorch and TensorFlow. Activeloop acts as a data lake for deep learning on unstructured data and offers in-browser dataset visualization, querying, and version control. On top of those features, Activeloop integrates with experimentation and labeling tools to allow rapid iteration on computer vision datasets.

Activeloop supports the following use cases:

Machine Learning teams can apply Activeloop's data infrastructure to ship their models fast in the following use cases:

1. AgriTech
2. Audio processing
3. Autonomous Vehicles & Robotics
4. Biomedical and Healthcare ML
5. Multimedia: Image enhancement, video enhancement, face detection, sports analytics, or machine learning for AR/VR
6. Safety & Security: surveillance machine learning with biometrics, facial recognition, or crowd counting

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