Detecting COVID-19 with Chest X-Ray using PyTorch
10.701 ya inscrito
10.701 ya inscrito
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.
En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:
Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.
En un video de pantalla dividida, tu instructor te guía paso a paso
por KO5 de oct. de 2020
My special thanks goes to Coursera and course supervisor
por TS27 de ago. de 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.
por AM4 de oct. de 2020
KUDOS TO THE INSTRUCTOR FOR A COMPREHENSIVE GUIDED MODULE.
por II22 de ago. de 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