For What?
Multimodal Data Infrastructure
Unified storage for text, images, video, and audio. Automatic versioning and indexing. Declarative preprocessing via computed columns.
Model Development
Define models as table operations. Supports custom Python UDFs. Integrates with popular ML frameworks. Automatic data lineage tracking.
Experiment Tracking
Version control for data and models. Compare experiments with table operations. Reproduce results through automatic lineage and provenance.
Incremental Pipelines
Efficient updates to data and models. Only recompute changed dependencies. Supports complex DAGs. Automatic caching and lazy evaluation.
For Who?
Computer Vision Engineers
Manage image and video datasets, annotations, and model inferences in one data infrastructure.
AI Developers
Declarative, incremental RAG pipelines and fine-tuning workflows, and document management.
Machine Learning Engineers
Ensure reproducibility, automate versioning, and simplify the path to production.
Data Scientists
Focus on insights, not infrastructure. Let Pixeltable handle the data plumbing across all modalities.
Documentation
API Reference
Contact
Open Source
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Friday, February 24 2023
📈 Folium: Create Web Maps From Your Data
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Pierre
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