Detecting COVID-19 with Chest X-Ray using PyTorch
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.
由 KO 提供Oct 5, 2020
My special thanks goes to Coursera and course supervisor
由 TS 提供Aug 27, 2020
It's a nice project, but I think more explanation about the concepts (ex- imagenet dataset, restnet18 model, etc.) must be provided to make the understanding more clearer.
由 II 提供Aug 22, 2020
Lecturer needs to let students know how to access dataset and code from in the beginning of the video lecture. It was hard to find code/ data download website
由 AM 提供Oct 4, 2020
KUDOS TO THE INSTRUCTOR FOR A COMPREHENSIVE GUIDED MODULE.