Pneumonia Classification using PyTorch
Offered By
In this Guided Project, you will:
fine tune EfficientNet Model
build a simple trainer to train the model
2 hours
Intermediate
No download needed
Split-screen video
English
Desktop only
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.
Skills you will develop
Deep Learning
Python Programming
Medical Imaging
pytorch
classification
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:
Configurations
Image Transformation and Load Dataset
Load dataset into batches
Fine Tuning EfficientNet Model
Build a Simple Trainer
Training Model
Plot Results
How Guided Projects 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
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