In the dynamic world of machine learning, two heavyweight frameworks often dominate the conversation: PyTorch and TensorFlow. These frameworks are more than just a means to create sophisticated ...

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.

If you actually need a deep learning model, PyTorch and TensorFlow are both good choices ...

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.

TensorFlow, PyTorch, Keras, Caffe, Microsoft Cognitive Toolkit, Theano and Apache MXNet are the seven most popular frameworks for developing AI applications.

When deploying large-scale deep learning applications, C++ may be a better choice than Python to meet application demands or to optimize model performance. Therefore, I specifically document my recent ...

Google enhances TensorFlow with deep learning capabilities and parallelism techniques for developer choice in machine language tooling.

PyTorch runs on Python and so is regarded to be a competitor to TensorFlow. Facebook has also open sourced its Horizon Reinforcement Learning (RL) products this year.

AI Platform Notebooks are configured with the core packages needed for TensorFlow and PyTorch environments. They also have the packages with the latest Nvidia driver for GPU-enabled instances.

If you are interested in building AI powered applications PyTorch is definitely worth checking out if Deep Learning something you would ...