data-versioning

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

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Distributed version-control for geospatial and tabular data

Open-source data management for multimodal AI. Query, trace, and govern with a lineage-native, format-agnostic lakehouse for agents and teams. Supports biological formats and registries - by the creators of Scanpy. 🍊YC S22

Metadata store for Production ML

Python framework for artificial text detection: NLP approaches to compare natural text against generated by neural networks.

Production-grade MLOps: Model deployment, monitoring, feature stores, and ML pipelines for real-world AI systems.

Python Data as Code core implementation

A demonstration of how DVC and MLFlow can be used in the task of data relabeling

A CKAN extension for data versioning.

Local content-addressed archive with observation history. Stores bytes by SHA-256, preserves locator state as contiguous spans, compresses with zstd and corpus-trained dictionaries. SQLite-backed.

Deprecated. See https://github.com/datopian/ckanext-versions. ⏰ CKAN extension providing data versioning (metadata and files) based on git and github.

Automatic data change tracking for SQLAlchemy

Automatic data change tracking for Django

Python Library that mantains ML pipelines with data checks, plots, training, and versioning. Check the clear documentation here:

Kedro-Dolt Hook Plugin

גרסאות לעם — מעקב גרסאות אחרי מאגרי מידע ממשלתיים פתוחים | over.org.il

This project demonstrates a complete workflow for analyzing sales data with missing values. It includes data cleaning, feature engineering, aggregation, and visualizations using Python libraries such as Pandas, NumPy, and Matplotlib.

Newron is a data-centric ML platform to easily build, manage, deploy and continuously improve models through data driven development.

The provided demo project demonstrates the practical implementation and advantages of using DVC. It showcases how DVC simplifies data versioning and model versioning while working in tandem with Git to create a cohesive version control system tailored for data science projects.