PyTorch surpasses its competitors by offering dynamic computation graphs, intuitive design, and seamless integration with Python, which ensures ease of use and unparalleled flexibility for developing deep learning models.
Apache MXNet is a lean, flexible, and ultra-scalable deep learning framework that supports state of the art in deep learning models, including convolutional neural networks (CNNs) and long short-term memory networks (LSTMs).
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors.
