Tutorial: Detecting COVID-19 with Chest X-Ray using PyTorch
Create custom Dataset and DataLoader in PyTorch
Train a ResNet-18 model in PyTorch to perform Image Classification
In this 2-hour long tutorial, 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 tutorial 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 tutorial, can not be used to diagnose COVID-19 or Viral Pneumonia. We are only using this data for educational purpose. Before you attempt this tutorial, 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 tutorial 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.
Skills you will develop
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction
Importing Libraries
Creating Custom Dataset
Image Transformations
Prepare DataLoader
Data Visualization
Creating the Model
Training the Model
Final Results
How Guided Tutorials work
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
Reviews
TOP REVIEWS FROM TUTORIAL: DETECTING COVID-19 WITH CHEST X-RAY USING PYTORCH
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.
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
Excellent course. My special thanks goes to Coursera and course supervisor
KUDOS TO THE INSTRUCTOR FOR A COMPREHENSIVE GUIDED MODULE.
Frequently asked questions
Frequently Asked Questions
What will I get if I purchase a Guided Tutorial?
Are Guided Tutorials available on desktop and mobile?
Who are the instructors for Guided Tutorials?
Can I download the work from my Guided Tutorial after I complete it?
What is the refund policy?
Is financial aid available?
Can I audit a Guided Tutorial and watch the video portion for free?
How much experience do I need to do this Guided Tutorial?
Can I complete this Guided Tutorial right through my web browser, instead of installing special software?
What is the learning experience like with Guided Tutorials?
More questions? Visit the Learner Help Center.
Coursera Footer
