There are 21 repositories under data-version-control topic.
Metrics Observability & Troubleshooting
sgr (command line client for Splitgraph) and the splitgraph Python library
A curated list to help you manage temporal data across many modalities 🚀.
Git based Version Control File System for joint management of code, data, model and their relationship.
Data version control for reproducible analysis pipelines in R with {targets}.
Meta data server & client tools for game development
SageMaker Experiments and DVC
Python framework for artificial text detection: NLP approaches to compare natural text against generated by neural networks.
create a robust, simple, effecient, and modern end to end ML Batch Serving Pipeline Using set of modern open-source/free Platforms/Tools
A CKAN extension for data versioning.
Metadata management in Go
Deprecated. See https://github.com/datopian/ckanext-versions. ⏰ CKAN extension providing data versioning (metadata and files) based on git and github.
A machine learning pipeline taking you from raw data to fully trained machine learning model - from data to model (d2m).
An abstraction layer for data storage systems
Python Data as Code core implementation
Data version control with Makefile and DVC for a regression task to estimate insurance costs for certain individuals.
Lesson 2 tutorial: Versioning Data and Model for the ML REPA School course: Machine Learning experiments reproducibility and engineering with DVC
Declaratively create, transform, manage and version ML datasets.
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.
Demonstration about how to use DVC(Data Version Control)
Deploying a Machine Learning Model on Heroku with FastAPI using CI/CD tools as GitHub Actions and Heroku Automatic Deployment.
The Chicken Disease Classification Using MLOps DVC Pipeline project utilizes the VGG16 architecture to analyze images of chicken fecal matter, enabling early disease detection and reducing economic losses in poultry farming.
📂 Comprehensive guide on using DVC for efficient and reproducible machine learning projects, covering essential commands and workflows.
In this repository, an ML-Ops task is undertaken to practice configuring and storing data using DVC on GitHub. The goal is to explore how DVC seamlessly integrates for efficient data management, enhancing reproducibility and scalability in machine learning workflows.
tutorial to connect dvc and aws-s3 and run github actions
tutorial to connect dvc and gdrive and run github actions
Data Version Control Pipeline assignment-6 from The School of AI EMLO-V4 course assignment https://theschoolof.ai/#programs
Data Version Control (DVC) , Hydra, Pytorch Lightning Integration MLOPS
Deploying a ML Model to Cloud Platform with FastAPI applying CI/CD practices