Open Source Framework

Apache MXNet is an open-source deep learning framework supporting multiple programming languages and devices, offering flexible programming models and efficient distributed training capabilities.

Caffe is an open-source deep learning framework developed by the University of California, Berkeley, known for its efficiency, flexibility, and modular design, widely used in image classification, speech recognition, and other fields.

MLX is an open-source framework developed by Apple's machine learning research team, designed specifically for Apple Silicon chips. It offers a NumPy-like API, supports automatic differentiation and lazy evaluation, aiming to assist developers in efficiently developing, training, and deploying machine learning models on Apple's M-series chips.