What to Consider with Model Ops When Moving to the Cloud?

Abstract: 

Cloud deployments are not the wave of the future – they’re the wave of today. And for all the right reasons, too! Greater speed, scale, agility, cost savings – so many benefits are gained ,. Organizations everywhere are moving more and more of their computing environment and inevitably. So to some degree, this process will come home to roost in your area and you will need to contend with making the switch and ensuring all of your goals for Model Ops and the benefits you get for building them into your analytics environment, do not get lost in the shuffle. Join in to hear Data Scientist and SAS Product Marketing Manager for Open Source and Data Science Marinela Profi share her ideas about how to make the transition and never miss a beat.

Bio: 

As a Marketing Manager for data science and open-source, Marinela uses her cross-domain expertise in statistics, business and marketing, to position SAS as a leader in the Data Science and Machine Learning Platform market. She focuses on helping customers apply advanced analytics, machine learning, natural language processing and forecasting to solve their most complex problems. Over the past 5 years, Profi honed her skills mining data, developing models and technical/business solutions, including deploying AI at scale. Her experience spans banking, manufacturing, retails and energy. She is a keynote speaker and presenter at different global conferences, where she shares trend and priorities of the data science industry. She is a published author, contributor to several eBooks, and blog writer on major industry and data science blogs. She has a bachelor’s in economics, an MBA and a master’s in statistics. She is passionate about getting more younger passionate to code and pursue careers in STEM.

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