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dvc-pipeline

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This repository offers a comprehensive solution for chest disease detection, covering data ingestion, preprocessing, model training, and CI/CD deployment pipelines. From raw data to automated deployment, streamline your chest disease detection process with our end-to-end solution.

  • Updated May 24, 2024
  • Python

Build end-to-end DL pipeline for computer vision (Image classification) for “Chest Disease Classification from Chest CT Scan Images” and deploy Flask web app to AWS EC2 with Docker and CI/CD tool: Jenkins

  • Updated May 22, 2024
  • Jupyter Notebook

Implemented research paper on UNETR on a custom multi-class dataset, built modular pipelines, served the model as REST API, developed the backend on Django REST Framework, deployed on AWS, developed frontend on Next.Js, deployed on Vercel. Implemented MLOps and DevOps.

  • Updated May 20, 2024
  • Jupyter Notebook

Implementation of MLops pipeline for Chest Disease Classification from Chest CT Scan Images using computer vision Vgg16 pretrained Image classification model. further perform deployment on AWS EC2 using Docker, CI/CD Jenkins tool, using Flask as front end interface.

  • Updated May 15, 2024
  • Jupyter Notebook

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