Beyond the hype: Transform your data science with MLOps
How MLOps empowers data science teams in insurance to achieve return on investment
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The machine learning opportunity is growing as insurers seek to unlock the value of their data, but only around 13% of data science projects ever make it into production. Data science teams are often siloed and don’t operate most productively in isolation.
This whitepaper is designed to share why data scientists often face issues, how MLOps could be the answer to scaling and achieving ROI with your data science efforts.
In this whitepaper, you’ll learn:
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Why many data scientists face roadblocks within insurance |
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How machine learning can increase value for insurers |
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Four insurance use cases |
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Tips on taking steps to progress in machine learning |
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With effective MLOps in place, what it can mean for insurers |
Who are Kainos?
At Kainos when we say "we do the difficult stuff", we really mean it. We understand the challenges data scientists face and help organisations to climb the Machine Learning Maturity scale from tactical to transformational. We leverage our experience building MLOps for leading insurers to drive business decisions based on your data science insights, helping your organisation unlock competitive advantage in a rapidly changing market.
Our tried and proven approach enables data science functions to bridge the gap between experimentation and business value, breaking down silos to operationalise and scale machine learning to benefit the entire business, all within 12 weeks, on average.
Download this whitepaper to kickstart your transformation journey
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