🔥PyTorch is an open-source framework for machine learning and deep learning.
✨PyTorch provides building blocks and functionalities for faster model training.
🚀PyTorch is easy to use, thanks to its Pythonic nature.
🤝PyTorch is supported by a dynamic community with open governance and a level playing field.
💡PyTorch is flexible and supports various platforms, including CPUs, GPUs, and mobile devices.
What is PyTorch?
—PyTorch is an open-source framework for machine learning and deep learning that provides building blocks and functionalities for model training.
Why is PyTorch popular?
—PyTorch is popular because it is easy to use, flexible, and supported by a dynamic community with open governance.
What platforms does PyTorch support?
—PyTorch supports various platforms, including CPUs, GPUs, and mobile devices.
How can I contribute to PyTorch?
—To contribute to PyTorch, you can sign the Contributor License Agreement (CLA), follow the code of conduct, and participate in the community through weekly office hours and Slack channels.
How is IBM contributing to PyTorch?
—IBM is contributing to PyTorch by using it in their projects and actively working on improvements, advancements, documentation, and supporting large-scale models and distributed training.
00:00PyTorch is the de facto standard for machine learning and deep learning.
00:16PyTorch is a framework that provides building blocks and functionalities for model training.
00:38PyTorch is an open-source project with a dynamic community and open governance.
00:58Key features of PyTorch include data sets, data loaders, and easy model building.
01:17PyTorch simplifies data preparation, provides iterators, and supports batch training.
02:14PyTorch helps with model training by providing loss functions, backward propagation, and optimization functions.
03:40Nonlinearity is added to models using activation functions provided by PyTorch.
05:37PyTorch is easy to use, thanks to its Pythonic nature and comprehensive documentation.
