The Google Brain team developed TensorFlow, an open-source machine learning library. It provides comprehensive support for building and deploying deep learning models.
PyTorch is an open-source deep learning library developed by Facebook’s AI Research lab (FAIR). It is known for its dynamic computational graph, making it more intuitive for many researchers.
Originally an independent library, Keras has been integrated into TensorFlow. It provides a high-level neural networks API that is user-friendly and can run on top of other deep learning libraries.
MXNet is an open-source deep learning framework that is designed for both efficiency and flexibility. It is supported by the Apache Software Foundation.
Theano is an open-source numerical computation library that is often used for deep learning. It allows for efficient computation on both CPUs and GPUs.
Torch is a scientific computing framework with wide support for machine learning algorithms. It has a Lua scripting language, but there is also a Python wrapper called torch7.
fastai is a high-level library built on top of PyTorch. It is designed to make deep learning more accessible by providing easy-to-use APIs and pre-built models.
Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center. It is known for its speed and efficiency, particularly in computer vision applications.
