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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.
Top-Bewertungen
KO
5. Okt. 2020
Excellent course.
My special thanks goes to Coursera and course supervisor
AM
4. Okt. 2020
KUDOS TO THE INSTRUCTOR FOR A COMPREHENSIVE GUIDED MODULE.
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