Transfer Learning in Image Recognition model in Deep Learning

What is Transfer Learning?

Transfer Learning is a powerful machine learning technique where a model trained for one task is adapted to perform another related task. It significantly reduces training time and improves model performance, especially when limited data is available.

Transfer learning, a key technique in image recognition. It’s part of a broader module on foundational concepts for building image recognition systems. Transfer learning leverages pre-trained models to improve efficiency and performance on new tasks, especially when data is limited.

Introduction :

Why transfer learning is important in image recognition. It saves time and computational resources by reusing models trained on large datasets like ImageNet, adapting them to specific tasks.

Introduction
├── Why Transfer Learning?
└── Benefits