What is Caffe?

Caffe (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework originally developed at the University of California, Berkeley. It is known for its speed and modularity, making it suitable for image classification and computer vision tasks. Caffe provides a clean and modifiable architecture, encouraging both application and research. Although development has slowed in recent years in favor of newer frameworks, it remains a valuable tool, particularly when computational efficiency is paramount.