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Machine Learning Engineering in Finance - Nemanja Radojkovic
Manage episode 398149982 series 2831626
Contenuto fornito da DataTalks.Club. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da DataTalks.Club o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
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/
Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html
176 episodi
Manage episode 398149982 series 2831626
Contenuto fornito da DataTalks.Club. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da DataTalks.Club o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
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/
Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html
176 episodi
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