Google Cloud AutoML Vision simplifies the creation of custom vision models for image recognition use-cases. The concepts of neural architecture search and transfer learning are used under the hood to find the best network architecture and the optimal hyperparameter configuration that minimizes the loss function of the model. This project uses Google Cloud AutoML Vision to develop an end-to-end medical image classification model for Pneumonia Detection using Chest X-Ray Images.

The dataset contains:

• 5,232 chest X-ray images from children.
• 3,883 of those images are samples of bacterial (2,538) and viral (1,345) pneumonia.
• 1,349 samples are healthy lung X-ray images.

The dataset is hosted on Kaggle and can be accessed at Chest X-Ray Images (Pneumonia).