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Alex Gold on DevOps for Data Science and Open Source Practices
Manage episode 451882670 series 3320043
A tartalmat a Data Driven biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Data Driven vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
Frank La Vigne sits down with Alex Gold, Head of Solutions Engineering at POSIT and author of "DevOps for Data Science."
Together, they explore the fascinating intersections of DevOps, MLOps, and generative AI, shedding light on the importance of social norms, innovation, and practical impact in open-source development.
Show Notes
Links
- DevOps for Data Science (Online Version) https://do4ds.com
- DevOps for Data Science (Amazon)
Moments
02:14 Marylander love their state flag
06:09 PBC prioritizes diverse responsibilities beyond shareholder value.
08:17 Chose Python for its versatility across fields.
12:15 Choose the right language for each pipeline stage.
16:14 Deploying software for enterprise use requires oversight.
19:26 Most data scientists rarely focus on machine learning.
23:18 Machine learning misunderstood; majority use simple models.
26:46 Generative AI in big companies, production challenges.
28:30 DevOps for data science needs unique practices.
31:28 Focus on quick wins for business value.
34:05 Focus on relationships; people problems require empathy.
37:17 Technical people focus on solving technical problems.
42:53 Companies exploring gen AI strategies, co-pilot model prioritized.
45:01 Exploring gen AI for effective customer data use.
49:32 Progress continues despite leveling off in horsepower.
52:40 AI needs deeper integration for life-changing impact.
55:39 Upload content; create NPR-style podcast summary.
58:38 Thanks for tuning in! Stay data driven.
300 epizódok
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