He, a research student at Cornell University, counted the number of papers discusing either PyTorch ... that TensorFlow is still the leader. The metrics used were: job listings, GitHub popularity ...

If this is what matters most for you, then your choice is probably TensorFlow. A network written in PyTorch is a Dynamic Computational Graph (DCG). It allows you to do any crazy thing you want to do.

it’s still far less mature than TensorFlow Lite. Finally, there’s the elephant in the room. PyTorch’s popularity in the past few years is almost certainly tied to the success of Hugging Face ...

In case you’re curious how TensorFlow’s graph execution works, it allows for optimizing computations and provides a clear overview of operations and dependencies. On the other side ...

Graph from StackOverflow trends ... and adopted many of PyTorch’s most popular features in TensorFlow 2.0. A good rule of thumb is that you can do anything that PyTorch does in TensorFlow.

As the popularity of the Python programming language persists, a user survey of search topics identifies a growing focus on AI and machine learning tasks and, with them, greater adoption of related ...

TensorFlow, which emerged out of Google in 2015, has been the most popular open source deep learning framework for both research and business. But PyTorch ... a knowledge graph that pulls together ...

It shares this space with another open-source machine-learning framework called PyTorch ... training or inference. Graphs: One of the reasons for TensorFlow’s popularity is its graph-based ...