Pneumonia Classification using PyTorch

提供方
Coursera Project Network
在此指導項目中,您將:

fine tune EfficientNet Model

build a simple trainer to train the model

Clock2 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

  • Deep Learning
  • Python Programming
  • Medical Imaging
  • pytorch
  • classification

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Configurations

  2. Image Transformation and Load Dataset

  3. Load dataset into batches

  4. Fine Tuning EfficientNet Model

  5. Build a Simple Trainer

  6. Training Model

  7. Plot Results

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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