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    Capital One’s Abhijit Bose on Best Practices for Machine Learning

    What are the most effective ways to manage your MLOps deployment?

    By
    James Maguire
    -
    December 20, 2022
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      I spoke with Abhijit Bose, Head of Enterprise Machine Learning and AI Engineering at Capital One, about how to optimize a machine learning deployment, from handling typical challenges to preparing for the future of MLOps.

      Among the topics we covered:

      • First let’s briefly define MLOps, machine learning to enhance operations. What’s your nutshell definition?
      • As you survey the business market, how would you describe the current MLOps adoption? In its infancy? Moving toward mainstream?
      • What are the most typical challenges that company face as they deploy MLOps?
      • A few best practices for MLOps?
      • The future of MLOps? What are some key milestones we can expect in the years ahead?

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      James Maguire
      James Maguire is eWeek's Editor-in-Chief and has been reporting on emerging technology for more than 15 years. He has won two ASBPE Awards of Excellence for in-depth feature articles about cloud computing and artificial intelligence. He has covered the gamut of enterprise and consumer technology, and regularly communicates with leading IT newsmakers, vendors and analysts.

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