Updated 3 days ago
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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
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To streamline the diagnostic process and help healthcare professionals
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
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In the realm of predictive analysis for Hill Valley, logistic regression is a statistical technique employed to forecast binary outcomes related to various factors in the region
dataset model classification tabular scikit-learn object detection image classification information retrieval anomaly detection git mlflow github
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End-to-end-Machine-Learning-Project-main provides version control, data pipeline, and enterprise-level ML application development.
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Aim to create a reliable skin cancer diagnosis model with extensive experimentation and handling imbalenced dataset.