November 05, 2018
ParallelM to Host Webinar on How to Take Machine Learning and Deep Learning Programs Into Production (Part 1 of 2)
BY MAGGIE MARKERT

Media Alert

WHAT: ParallelM, a rapidly growing company in the machine learning operationalization (MLOps) space, will host a webinar,Bringing Machine Learning & Deep Learning Algorithms to Life: From Experiments to Production Use (Part I of II),” for data scientists.

In this two-part webinar, data scientists will learn how to take machine learning (ML) and deep learning (DL) programs into a production use case and manage the full production lifecycle.

Part I of the webinar will explore the following:

  • DL application deployment
  • Monitoring
  • DL application health
  • Canary models

WHO: Nisha Talagala, CTO and VP of Engineering at ParallelM

WHEN: Tuesday, November 13, 2018, at 10:00am PT

WHERE: https://zoom.us/webinar/register/6415405902668/WN_AgzL8_a0TsaEHA19mRulCg

WHY: For many data scientists, the deployment of machine learning into production environments has remained a challenge. Current IT and operations teams along with the tools can’t account for the complexities of deploying, managing and scaling ML applications, leaving data science and data engineering teams responsible for the success – or failure – of ML and AI initiatives. Data scientists must learn how to bring their promising experimental results on ML and DL algorithms into production success.

About ParallelM:

ParallelM is the first and only company completely focused on delivering machine learning operationalization (MLOps) at scale. ParallelM’s breakthrough MCenter™ solution is built specifically to power the deployment and management of machine learning pipelines in production so that companies can scale machine learning delivery across their business applications. ParallelM’s approach is that of a single, unified MLOps solution that embeds best practice processes in technology, enabling greater productivity across all ML stakeholders to unlock the business value of AI. To learn more, visit www.parallelm.com and mlops.org.

ParallelM and MCenter are trademarks of Parallel Machines, Inc. All other trademarks are the property of their respective registered owners. Trademark use is for identification only and does not imply sponsorship, affiliation, or endorsement.

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