Visual Studio Code, a free cross-platform lightweight code editor, has become the most popular among Python developers for both web and machine learning projects. We will be walking you through an end-to-end PyTorch project to showcase what VS Code has a lot to offer to PyTorch developers to boost their productivity.
Firstly, get your PyTorch project quickly up and running with VS Code’s environment/dependency management and built-in Jupyter Notebook support. Secondly, breeze through coding with help from our AI-powered IntelliSense. When it’s time to run your code, use the built-in Tensorboard integration to monitor your training along with the integrated PyTorch profiler to analyze and debug your code. Once you’re ready for the cloud, VS Code has Azure service integration to allow you to scale your model training and deployment, along with deployment.
Combing the power of the code editor with easy access to the Azure services, VS Code can be the one-stop-shop for any developers looking to build machine learning models with PyTorch.
Program Manager at Microsoft
Jeffrey Mew is a Program Manager at Microsoft working on the Python Data Science and AI experience in VS Code. Specifically, he is focusing on PyTorch tooling and making the lives of Data Scientists easier across our ecosystem. Jeffrey holds his Bachelor’s Degree in Computer Engineering from the University of Waterloo. He is a lover of dogs and Python (the language, still unsure about the snake).
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PyTorch development in VS Code
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