Updated 3 days ago
Path: .
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
Updated 1 week ago
Path: data
1000 Images from COCO dataset with polygon segmentation
dataset computer vision semantic segmentation object detection dvc git mlflow ultralytics yolo
Path: .
Aim to create a reliable skin cancer diagnosis model with extensive experimentation and handling imbalenced dataset.
Updated 1 month ago
Updated 2 months ago
Path: .
A DVC tracked version of COCO 2017, including the train and test set
dataset computer vision semantic segmentation object detection dvc git
Updated 3 months ago
Path: .
Showcasing DagsHub Annotations, Label Studio integration, Discussions, and other related features
Updated 3 months ago
Path: .
chest cancer detection using mlflow and dbc
dataset model computer vision tensorflow image classification dvc git mlflow github
Path: .
This Malaria Cell Classification Using Deep Learning Technique
dataset computer vision classification dvc git mlflow github
Updated 4 months ago
Path: . s3:/DagsHubDrive/datasets/coco
An example project showing how to use DagsHub with the new built-in S3 bucket per repo
Updated 7 months ago
Path: src/data
Open Source Data Science (OSDS) Monocular Depth Estimation – Turn 2d photos into 3d photos – show your grandma the awesome results.
dataset model computer vision depth estimation dvc git mlflow google cloud storage
Updated 8 months ago
Updated 8 months ago