Training PyTorch Models on Azure

Azure

Microsoft Azure is a cloud computing platform that provides a wide range of services such as computing power, storage, and databases to businesses and individuals. Azure is known for its scalability, reliability, and security. It offers a pay-as-you-go pricing model which allows users to only pay for the services they use. Azure is used by many companies such as BMW, Samsung, and GE Healthcare.

PyTorch Models

PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing. It was originally developed by Meta AI and now part of the Linux Foundation umbrella. PyTorch is designed to provide good flexibility and high speeds for deep neural network implementation. PyTorch uses dynamic computation graphs which makes it different from other deep learning frameworks. It has become a popular choice for deep learning tasks such as computer vision, natural language processing, and speech recognition. PyTorch has gained popularity for its simplicity, ease of use, dynamic computational graph, efficient memory usage, flexibility, speed, native ONNX model exports, which can be used to speed up inference. It also shares many commands with numpy which reduces the barrier to learning it.
Azure is a popular cloud option for companies looking to deploy PyTorch models at scale. Kaspian securely deploys into your Azure environment, ensuring that all storage and compute assets remain within your cloud. Kaspian's flexible compute layer empowers data teams to train PyTorch models on Azure in a highly performant, scalable, and configurable manner, with native support for autoscaling, GPU acceleration, and more.
Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.

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