Pneumonia Classification using PyTorch
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.
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- Level Intermediate
- Duration 2 hours
- Course by Coursera Project Network
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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.Modules
Pneumonia Classification using PyTorch
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- Graded Quiz: Pneumonia Classification using PyTorch
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- Pneumonia Classification using PyTorch
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- Project-based Course Overview
Auto Summary
Dive into the world of deep learning with the engaging "Pneumonia Classification using PyTorch" course. This hands-on guided project, designed for personal development, spans 2 hours and focuses on utilizing the EfficientNet model to train on a comprehensive Pneumonia Chest X-Ray dataset comprising nearly 5600 images categorized into Pneumonia and Normal classes. Throughout the course, you will learn to load and fine-tune a pretrained EfficientNet model and create a simple PyTorch trainer to effectively train the model. This project emphasizes practical implementation over theoretical knowledge, making it ideal for professionals familiar with Python, convolutional neural networks, and basic PyTorch. Offered by Coursera, this professional-level course is available under the Starter subscription. While it currently provides the best experience for learners in North America, efforts are underway to enhance accessibility for other regions. Perfect for those looking to expand their machine learning and PyTorch skills, this course promises a rich, hands-on learning experience that equips you with the expertise needed to build a robust pneumonia classifier.
Parth Dhameliya