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Using PyTorch to streamline machine-learning projects A platform that lets surgeons browse videos of past operations has found a way to make its machine learning more effective.
PyTorch is an open-source machine learning library developed by Facebook’s AI Research lab (FAIR). It’s known for its flexibility, ease of use, and as a powerful tool for deep learning ...
Python’s traditional role in machine learning has been to wrap high-speed, back-end code libraries with easy-to-use, front-end syntax.
Both PyTorch and TensorFlow support deep learning and transfer learning. Transfer learning, which is sometimes called custom machine learning, starts with a pre-trained neural network model and ...
PyTorch, which Facebook publicly released in October 2016, is an open source machine learning library based on Torch, a scientific computing framework and script language that’s in turn based on ...
Dr. James McCaffrey of Microsoft Research provides a full code sample and screenshots to explain how to create and use PyTorch Dataset and DataLoader objects, used to serve up training or test data in ...
In the realm of machine learning frameworks, there’s no one-size-fits-all solution. PyTorch and TensorFlow offer distinct advantages that cater to different aspects of the machine learning workflow.
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 ...
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