Speed Up Machine Learning Training on CPUs with AI Tools
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Overview
Speed up tasks such as data preprocessing at scale, training, and inference while also gaining performance.
This session explores how two AI Tools can be used as drop-in replacements for stock pandas and scikit-learn* libraries to significantly speed up key tasks in machine learning model development and deployment on CPUs instead of GPUs.
- Modin* enables data scientists to scale to distributed DataFrame processing without having to change API code.
- Intel® Extension of Scikit-learn* seamlessly accelerates scikit-learn applications for Intel CPUs and GPUs across single- and multi-node configurations.
This session covers an overview of these tools including:
- An overview of the tools—Modin and Intel Extension for Scikit-learn—and what you can do with them
- How to use Modin as a drop-in replacement for stock pandas
- How to use the scikit-learn extension as a drop-in replacement for stock scikit-learn libraries
- A live demo showcasing the performance improvements.
Skill level: Novice
Featured Software
Get the following tools as stand-alone versions from GitHub* or as part of AI Tools.
Download Code Samples
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