Enhance and Accelerate Microsoft Azure* Machine Learning Workloads
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Overview
Two problems continuously faced by machine learning engineers and data scientists are:
- Efficiently managing AI pipelines from development to deployment.
- Running those pipelines in such a way as to reduce costs and resource use.
Microsoft* and Intel collaborated to create a solution that addresses both by incorporating Intel® AI optimizations into the Microsoft Azure* Machine Learning platform. Sign up for this session to learn what it is and how to take advantage of it.
This session provides:
- An overview of the solution, which integrates Intel optimizations for Python* frameworks such as PyTorch*, TensorFlow*, and scikit-learn* on the Azure Machine Learning platform
- How to enable the solution in your Azure workloads using the previously mentioned framework optimizations to reduce cloud costs and development time, increase resource use, and improve machine learning pipeline speed
Includes a demo.
Skill level: Intermediate
Featured Software
Get the following stand-alone extensions from Intel on GitHub* or as part of the Intel® AI Analytics Toolkit.
Download Code Samples
Accelerate data science and AI pipelines-from preprocessing through machine learning-and provide interoperability for efficient model development.
Speed up and scale your scikit-learn* workflows for CPUs and GPUs across single- and multi-node configurations with this Python* module for machine learning.
TensorFlow* has been directly optimized for Intel® architecture, in collaboration with Google*, using the primitives of Intel® oneAPI Deep Neural Network Library (oneDNN) to maximize performance. The Intel® AI Analytics Toolkit (AI Kit) provides the latest binary version compiled with CPU-enabled settings, along with Intel® Extension for TensorFlow*, which seamlessly plugs into the stock version to add support for new devices and optimizations.
Intel is one of the largest contributors to PyTorch*, providing regular upstream optimizations to the PyTorch deep learning framework that provide superior performance on Intel® architectures. The AI Tools includes the latest binary version of PyTorch tested to work with the rest of the kit, along with Intel® Extension for PyTorch*, which adds the newest Intel optimizations and usability features.
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