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



What is Pandas? 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.

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 or 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 run end-to-end machine learning workloads efficiently without any code changes

    Get the Software

  • Download the Intel® Distribution of Modin* as part of the Intel® oneAPI AI Analytics Toolkit. Powered by oneAPI, the AI Kit includes six development tools for accelerating data science and AI pipelines.
  • Sign up for an Intel® DevCloud for oneAPI account—a free development sandbox with access to the latest Intel® hardware and oneAPI software, including the AI Toolkit.

    Other Resources

  • OmniSci and Intel Collaborate to Bring Accelerated Analytics at Scale to CPUs
  • Read the latest AI Analytics blogs on Medium.
  • Subscribe to the POD—Code Together is an interview series that explores the challenges at the forefront of cross-architecture development. Each biweekly episode features industry VIPs who are blazing new trails through today's data-centric world. Available wherever you get your podcasts.

Areg Melik-Adamyan
Software engineering manager, Intel Corporation

Areg Melik-Adamyan is an engineering manager and architect with over 20 years' experience in cross-architecture software development. Joining Intel in 2011, he works on next-generation data analytics, both software and its deployment across heterogeneous platforms. Areg holds a PhD in computer science from the Russian Academy of Sciences in Moscow and an MS from Yerevan State University, Armenia


Intel® oneAPI AI Analytics Toolkit

Accelerate end-to-end machine learning and data science pipelines with optimized deep learning frameworks and high-performing Python* libraries.


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