PyTorch 1.10 is production ready, with a rich ecosystem of tools and libraries for deep learning, computer vision, natural language processing, and more. Here's how to get started with PyTorch.

TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models. Topics Spotlight: New Thinking about Cloud Computing ...

PyTorch is an open source machine learning framework used for developing deep learning models. Originally created by Meta AI ...

In collaboration with the Metal engineering team at Apple, PyTorch today announced that its open source machine learning framework will soon support GPU-accelerated model training on Apple silicon ...

Using a mix of PyTorch, a framework co-created by Facebook, and machine-learning platform Allegro Trains, med-tech company theator is now providing surgeons with a tool that lets them watch over ...

Soumith Chintala from Facebook AI Research, PyTorch project lead, talks about the thinking behind its creation, and the design and usability choices made. Facebook is now unifying machine learning ...

PyTorch was born at Facebook in 2018 as a unified machine learning framework. It was created as a successor to Caffe2, one of the popular ML frameworks for building deep learning models. The ...

Scikit-learn is a library with many uses, such as for classical machine learning algorithms, like those for spam detection, image recognition, prognostication, and customer segmentation.

Developers can submit ML training jobs created in TensorFlow, Keras, PyTorch, Scikit-learn, and XGBoost. Google now offers in-built algorithms based on linear classifier, wide and deep and XGBoost ...