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https://github.com/jisnap/dvc_pipeline

This repository manages multiple datasets and ML models using DVC
https://github.com/jisnap/dvc_pipeline

dvc dvc-pipeline

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This repository manages multiple datasets and ML models using DVC

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Overview

This project demonstrates how to use DVC (Data Version Control) with Git Tags to manage different versions of datasets and models. By leveraging git checkout and dvc checkout, you can seamlessly switch between different versions of data and models while maintaining reproducibility.

Prerequisites

Ensure you have the following installed:

Git

DVC (pip install dvc)

A remote storage (Google Drive, S3, Azure, or a local path) for DVC data tracking

This repository uses https://github.com/iterative/example-versioning and this has been created for thoroughly understanding how dvc can be used for version control data ,model and pipelines.