TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models.

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.

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 ...

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 ...

IBM Research has contributed code to the open-source PyTorch machine learning project that could help to significantly accelerate training.