TensorFlow is an open source software library developed by Google for numerical computation with data flow graphs. This TensorFlow guide covers why the library matters, how to use it and more.

TensorFlow is your ally for scalability and production. PyTorch is your friend for research flexibility and ease of use. The choice depends on your project needs, expertise, and long-term goals.

PyTorch recreates the graph on the fly at each iteration step. In contrast, TensorFlow by default creates a single data flow graph, optimizes the graph code for performance, and then trains the model.

No longer the upstart nipping at TensorFlow’s heels, PyTorch is a major force in the deep learning world today, perhaps primarily for research, but also in production applications more and more.

Is PyTorch better than TensorFlow for general use cases? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world ...

This article will discuss the seven popular tools and frameworks used for developing AI applications: TensorFlow, PyTorch, Keras, Caffe, Microsoft Cognitive Toolkit, Theano and Apache MXNet.