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14
October 2020
11:00 am
Public Event

Achieve High-Performance Scaling for E2E Machine Learning and Data Analytics Workflows

Sponsored By
Intel
ATTEND
Chicago

If your software applications rely on compute-intense math routines, you’re well aware how important a comprehensive math library is. This webinar demonstrates the power of one ofthe world’s best: Intel® oneAPI Math Kernel Library (oneMKL).

WTH is Pandas?

Well, they’re super cute tuxedo-colored bears from China who have six toes and eat bamboo.

Also … Pandas is dataframe library that allows to you perform data manipulation in Python, and it’s great for heterogeneous data—think data science—because it provides easy-to-use APIs to manipulate and process dataframes.

(You knew we’d get there.)

But there’s an issue: When working with excessively large amounts of data or when needing high-performance, single-core Pandas becomes a bottleneck for a data practitioner’s workflow. As a result, adopting a Pandas-workflow-compatible distributed system/solution is often needed.

This webinar discusses precisely that: Intel® Distribution of Modin*.

Join software engineer Areg Melik-Adamyan for a tour of this Distribution, including:

  • An overview Modin, including its OmniSci (accelerated analytics) back end
  • How to get the best performance and scaling through Intel Distribution of Modin
  • How to efficiently run end-to-end machine learning workloads without any code changes