Detecting COVID-19 with Chest X-Ray using PyTorch

4.5
별점

323개의 평가

제공자:

10,711명이 이미 등록했습니다.

학습자는 이 안내 프로젝트에서 다음을 수행하게 됩니다.
2 hours
중급
다운로드 필요 없음
분할 화면 동영상
영어
데스크톱 전용

In this 2-hour long guided project, we will use a ResNet-18 model and train it on a COVID-19 Radiography dataset. This dataset has nearly 3000 Chest X-Ray scans which are categorized in three classes - Normal, Viral Pneumonia and COVID-19. Our objective in this project is to create an image classification model that can predict Chest X-Ray scans that belong to one of the three classes with a reasonably high accuracy. Please note that this dataset, and the model that we train in the project, can not be used to diagnose COVID-19 or Viral Pneumonia. We are only using this data for educational purpose. Before you attempt this project, you should be familiar with programming in Python. You should also have a theoretical understanding of Convolutional Neural Networks, and optimization techniques such as gradient descent. This is a hands on, practical project that focuses primarily on implementation, and not on the theory behind Convolutional Neural Networks. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

개발할 기술

  • Deep Learning

  • Machine Learning

  • Statistical Classification

  • Medical Imaging

  • pytorch

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

검토

DETECTING COVID-19 WITH CHEST X-RAY USING PYTORCH의 최상위 리뷰

모든 리뷰 보기

자주 묻는 질문