Session

Morning Session

17 Nov 2020, 09:15

Description

We will provide an overview on the most known machine learning algorithms for supervised and unsupervised learning. With small example codes we show how to implement such algorithms using the Intel® Distribution for Python*, and which performance benefit can be obtained with minimal effort from the developer perspective.

Presentation materials

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  1. 17/11/2020, 09:15
    • Intel’s Hardware and Software directions for Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL)
    • Hardware Accelerated Deep Learning instructions and implementations, DL Boost, VNNI instructions
    • oneAPI Tools Framework delivering Intel AI development tools
    Go to contribution page
  2. 17/11/2020, 10:30
    • Python Demos with focus on Classical Machine Learning examples and algorithms
    • Data Analysis and preparation with Modin -- a new library designed to accelerate Pandas by automatically distributing the computation across all of system's available CPUs
    Go to contribution page
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