If you’re looking to explore deep learning in general using PyTorch, I recommending having a look at the fast.ai course. It will take you through the theory of deep learning and its applications ...

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.

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 ...

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

We call ML outputs predictions, but they can be anything. If you’re using computer vision, they can be identified objects. If you’re using a language model, they’re intent or translations.

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 ...

Combining PyTorch with Microsoft Azure Machine Learning, AstraZeneca's technology can comb through massive amounts of data to gain new insights about the complex links between drugs, diseases ...

Is PyTorch better than TensorFlow for general use cases? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world ...