'The 20% of problems which are hard to solve but have really big returns, that’s probably where data scientists need to be focusing their effort because trying to scale machine learning models across thousands of thousands of failure modes in a plant is probably not practical in the traditional approach to data science.'
- Denis Marshment
VROC was pleased to host Accelerating Industrial Data Science, an industry event as part of Data Science Week 2021. The event focused on the challenges experienced in scaling data science and the emerging opportunities of growth in this area. We invite you to re-watch this event, which provides a robust update on where industrial data science solutions are headed and how we can accelerate growth to ensure industry experiences real value from data analytics, data science and auto-machine learning.
Topic Covered:
Who should Watch:
Denis Marshment is the former global vice president of data science customer solutions at Worley. His specialities include but are not limited to, Asset Management consulting, strategy development, performance improvement and reliability solution implementation.
Sia is a Mechanical Engineer with over 10 years of experience in oil and gas downstream equipment design. He is an expert Data Analyst/Scientist with extensive experience in asset health and integrity data analytics, risk/failure mode analysis and prediction, production/operation optimisations, process automation, consumer behaviour and market studies in both academic and industrial environments.
Arvind brings to table 4 decades of energy industry experience. With an M.S. in Mechanical Engineering, Arvind has held technical roles worldwide for companies including SCANA Corporation and Schlumberger, following which he switched focus to Business Development.
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The efficient deployment, continuous retraining of models with live data and monitoring of model accuracy falls under the categorisation called MLOps. As businesses have hundreds and even.
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