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Coursera Project Network

Pneumonia Classification using PyTorch

Coursera Project Network via Coursera

Overview

In this 2-hour guided project, you are going to use EfficientNet model and train it on Pneumonia Chest X-Ray dataset. The dataset consist of nearly 5600 Chest X-Ray images and two categories (Pneumonia/Normal). Our main aim for this project is to build a pneumonia classifier which can classify Chest X-Ray scan that belong to one of the two classes. You will load and fine tune the pretrained EffiecientNet model and also to create a simple pytorch trainer to train the model. In order to be successful in this project, you should be familiar with python, convolutional neural network, basic pytorch. 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.

Syllabus

  • Project Overview
    • In this project, you are going to use EfficientNet model and train it on Pneumonia Chest X-Ray dataset. The dataset consist of nearly 5600 Chest X-Ray images and two categories (Pneumonia/Normal). Our main aim for this project is to build a pneumonia classifier which can classify Chest X-Ray scan that belong to one of the two classes. You will load and fine tune the pretrained EffiecientNet model and also to create a simple pytorch trainer to train the model.

Taught by

Parth Dhameliya

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4.3 rating at Coursera based on 10 ratings

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