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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.

Status: Transfer Learning
Status: Model Evaluation
IntermediateGuided Project2 hours

Featured reviews

TS

4.0Reviewed 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.

ID

4.0Reviewed 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

BM

5.0Reviewed Oct 4, 2020

KUDOS TO THE INSTRUCTOR FOR A COMPREHENSIVE GUIDED MODULE.

TJ

5.0Reviewed Jan 23, 2022

Good explanations + code. Everything so smooth and understandable. Great lector!

EK

5.0Reviewed Oct 5, 2020

Excellent course.My special thanks goes to Coursera and course supervisor

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