TensorFlow also lost steam in the research community, which started preferring the flexibility PyTorch offered a few years ago, resulting in a decline in the use of TensorFlow in research papers.

Is PyTorch better than TensorFlow for general use cases? This question was originally answered on Quora by Roman Trusov.

Many developers who use Python for machine learning are now switching to PyTorch. Find out why and what the future could hold for TensorFlow.

Both PyTorch and TensorFlow support deep learning and transfer learning. Transfer learning, which is sometimes called custom machine learning, starts with a pre-trained neural network model and ...

This PyTorch vs TensorFlow guide will provide more insight into both but each offers a powerful platform for designing and deploying machine learning models.

There are tools to convert Tensorflow, PyTorch, XGBoost, and LibSVM models into formats that CoreML and ML Kit understand. But other solutions try to provide a platform-agnostic layer for training ...

Microsoft is stepping up its support for enterprise customers that are using Facebook's PyTorch deep-learning framework on the Microsoft Azure cloud. Microsoft has been contributing to the open ...

TensorFlow Lite (TFLite) was announced in 2017 and Google is now calling it “LiteRT” to reflect how it supports third-party models. TensorFlow Lite for mobile on-device AI has “grown beyond ...