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This project provides a comprehensive guide on using DagsHub to manage machine learning datasets and models. It includes steps for setting up a DagsHub project, connecting data buckets, creating datasets, annotating data, fine-tuning models, tracking experiments, registering models, and logging predictions. The guide is supplemented with visual aids to help users follow along easily.
dataset computer vision object detection git mlflow s3 compatible storage