Detecting COVID-19 with Chest X-Ray using PyTorch
324 ratings

10,989 already enrolled
Create custom Dataset and DataLoader in PyTorch
Train a ResNet-18 model in PyTorch to perform Image Classification
324 ratings
10,989 already enrolled
Create custom Dataset and DataLoader in PyTorch
Train a ResNet-18 model in PyTorch to perform Image Classification
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.
Deep Learning
Machine Learning
Statistical Classification
Medical Imaging
pytorch
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
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
by TS
Aug 27, 2020It'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.
by KO
Oct 5, 2020Excellent course.
My special thanks goes to Coursera and course supervisor
by II
Aug 22, 2020Lecturer 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
by AM
Oct 4, 2020KUDOS TO THE INSTRUCTOR FOR A COMPREHENSIVE GUIDED MODULE.
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
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Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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