Machine Learning 101 with Python and daal4py

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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David Liu, Technical Consulting Engineer, Intel Corporation

David Liu is a Lead Python* Technical Consulting Engineer who specializes in open source software development and focuses on machine learning, deep learning, AI, software architecture and build infrastructure. In his current role, he is responsible for assisting customers and the open-source community in all phases of improving software quality and optimizing it for Intel hardware. David joined Intel in 2015 and holds a Master’s of Science in Software Engineering from the University of Texas, Austin.

Performance varies by use, configuration, and other factors. Learn more at www.Intel.com/PerformanceIndex.