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

Metadata store for Production ML

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

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

Python Data as Code core implementation

A CKAN extension for data versioning.

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 Django

Automatic data change tracking for SQLAlchemy

Kedro-Dolt Hook Plugin

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

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.

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.

Production-ready ML pipeline solving reproducibility challenges with DVC, docker, MLflow & DagHub

Testing and implementations with ClearML

Deploying a ML Model to Cloud Platform with FastAPI applying CI/CD practices

Project with tabular data versioned with Artifacts.

A template for building governed and reproducible machine learning projects, enabling transparent tracking of data, models, and deployments across various platforms.