Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

How to use PyTorch At the heart of PyTorch are tensors, which are similar to advanced arrays that you might be familiar with from NumPy, but with the added capability of running on GPUs.

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.

Understand how Intersection over Union (IoU) works and how to implement it using PyTorch. This metric is essential for ...

Regression Using PyTorch, Part 1: New Best Practices Machine learning with deep neural techniques has advanced quickly, so Dr. James McCaffrey of Microsoft Research updates regression techniques and ...

When using a PyTorch neural network, categorical predictor data must be encoded into a numeric form, and numeric predictor data should be normalized. For multi-class classification, the dependent ...

AstraZeneca is using PyTorch-powered algorithms to discover new drugs The pharmaceutical firm has revealed how it is using sophisticated machine-learning tools to speed up drug discovery.

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.

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