Keras Applications

Keras Applications is a module within the Keras deep learning library that provides pre-trained models for computer vision tasks, such as image classification, object detection, and feature extraction. These models are trained on large datasets like ImageNet and can be used for transfer learning, fine-tuning, or as feature extractors. It simplifies the process of leveraging state-of-the-art architectures without requiring extensive training from scratch.

Also known as: Keras Pretrained Models, Keras Model Zoo, Keras Pre-trained, Keras App, Keras Applications Module

Why learn Keras Applications?

Developers should use Keras Applications when building computer vision applications that require high accuracy with limited training data or computational resources, as it enables efficient transfer learning. It is particularly useful for tasks like image classification, object recognition, and medical imaging, where pre-trained models can be fine-tuned on domain-specific datasets to achieve robust performance quickly.

Learning Resources

• docs: Keras Applications Documentation
• tutorial: Transfer Learning with Keras Applications Tutorial
• book: Deep Learning with Python Book by François Chollet
• video: Keras Applications Video Tutorial by Sentdex
• course: Coursera Deep Learning Specialization