MLOps Industry Insights
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Company you work for
Where are you located? *
What is your primary role in your company? *
Number of employees of your company *
How big is the data science / ML team within your company? *
In which industry is your current company?
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What type(s) of ML do you do? *
Required
Do you currently use any MLOps tools or platforms? If yes, which ones?
What are the biggest challenges you face in managing the ML lifecycle?
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Required
Do you use cloud-based development environments?
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What features do you consider essential in a development environment tool?
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Required
How do you currently manage collaboration within your data science team?
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Do you use shared storage solutions for datasets? If yes, what features do you find most useful?
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How important is it for you to have auto-scaling capabilities for deployed models? *
Not important at all
Extremely important
Do you use any form of feature flags or A/B testing for model deployment?
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How do you currently monitor the performance of deployed models?
What is your typical response strategy when a deployed model starts to underperform?
What features would you like to see in an MLOps tool?
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Would you be willing to try out our product KeaML? If so, please share your email address
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