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DataTalks.Club

Machine Learning Engineering in Finance - Nemanja Radojkovic

Jan 31, 2024
53:10

We talked about:

  • Nemanja’s background
  • When Nemanja first work as a data person
  • Typical problems that ML Ops folks solve in the financial sector
  • What Nemanja currently does as an ML Engineer
  • The obstacle of implementing new things in financial sector companies
  • Going through the hurdles of DevOps
  • Working with an on-premises cluster
  • “ML Ops on a Shoestring” (You don’t need fancy stuff to start w/ ML Ops)
  • Tactical solutions
  • Platform work and code work
  • Programming and soft skills needed to be an ML Engineer
  • The challenges of transitioning from and electrical engineering and sales to ML Ops
  • The ML Ops tech stack for beginners
  • Working on projects to determine which skills you need


Links:

  • LinkedIn: https://www.linkedin.com/in/radojkovic/

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