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学生对 Coursera Project Network 提供的 Detecting COVID-19 with Chest X-Ray using PyTorch 的评价和反馈

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323 个评分

课程概述

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....

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KO

Oct 5, 2020

Excellent course.

My special thanks goes to Coursera and course supervisor

AM

Oct 4, 2020

KUDOS TO THE INSTRUCTOR FOR A COMPREHENSIVE GUIDED MODULE.

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1 - Detecting COVID-19 with Chest X-Ray using PyTorch 的 25 个评论(共 38 个)

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