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Machine Learning 101 with Python and daal4py

Join Intel Technical Consulting Engineer David Liu, for an overview of Intel’s Python distribution and daal4py package

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Machine learning (ML) is far past being merely a buzz word. It’s matured into a major disruptor, profoundly impacting business and transforming how we interact in the world and with each other.

For software developers, it’s increasingly becoming a major differentiator that leads to the obvious question: How do you increase your machine learning performance?

One way is by using the Intel® Distribution for Python*—a set of accelerated numeric Python packages, including scikit-learn, NumPy, SciPy, and daal4py, all optimized to work in both single and distributed modes.

Join Intel Technical Consulting Engineer David Liu, for an overview of Intel’s Python distribution and daal4py package, including:

  • How they can decrease your ML compute time
  • Where and when to use daal4py in your ML application
  • The new High-Performance Analytics Toolkit (HPAT) feature and how it accelerates getting data into your ML app

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


About the Author

Intel Corporation
United States United States
You may know us for our processors. But we do so much more. Intel invents at the boundaries of technology to make amazing experiences possible for business and society, and for every person on Earth.

Harnessing the capability of the cloud, the ubiquity of the Internet of Things, the latest advances in memory and programmable solutions, and the promise of always-on 5G connectivity, Intel is disrupting industries and solving global challenges. Leading on policy, diversity, inclusion, education and sustainability, we create value for our stockholders, customers and society.
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Posted 9 Oct 2019


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