Which of these deep learning frameworks should you use? In this article, we’ll take a high-level comparative look at TensorFlow, PyTorch, and JAX.

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.

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

I’ve previously reviewed PyTorch 1.0.1 and compared TensorFlow and PyTorch. I suggest reading the review for an in-depth discussion of PyTorch’s architecture and how the library works.

What is PyTorch? PyTorch is a deep learning framework designed to simplify AI model development. First released by Meta AI, it was built to improve the flexibility of deep learning research.

An article that was recently published on the gradient is examining the current state of Machine Learning frameworks in 2019. The article is utilizing some metrics to argue the point that PyTorch ...

TensorFlow is Google's open-source AI framework used for machine learning and deep learning applications.

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

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

First is PyTorch, with its tremendous following and mindshare. If you look at the metrics alone it might be easy to miss, but PyTorch is quite possibly the most used and talked about deep learning ...