Artwork

Innehåll tillhandahållet av Klaviyo Data Science Team. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Klaviyo Data Science Team eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.
Player FM - Podcast-app
Gå offline med appen Player FM !

Klaviyo Data Science Podcast EP 38 | Production 101

42:01
 
Dela
 

Manage episode 373806168 series 3251385
Innehåll tillhandahållet av Klaviyo Data Science Team. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Klaviyo Data Science Team eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

An introduction to production

What comes after you finish building a data science model? If you’re working on a software project, the answer likely involves that model serving customers in production. Understanding production is crucial for any data scientist or software engineer, so we spend this episode learning about best practices from three experienced Klaviyo engineers.

Listen along to learn more about:

  • How to make sure your code is “battle-ready,” whether you’re working on a data science project or not
  • Why error messages you think are safe to ignore may not actually be safe to ignore
  • One key lesson for safely deploying your code, no matter what environment you work in

“That’s stuck with me through the years: there are these knock-on effects between things. Even if it’s not your code, you should still try to understand how it’s working and whether it can have a ripple effect that comes back and affects your code.”— Chris Conlon, Lead Software Engineer

Check out the full show notes on Medium!

  continue reading

47 episoder

Artwork
iconDela
 
Manage episode 373806168 series 3251385
Innehåll tillhandahållet av Klaviyo Data Science Team. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Klaviyo Data Science Team eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

An introduction to production

What comes after you finish building a data science model? If you’re working on a software project, the answer likely involves that model serving customers in production. Understanding production is crucial for any data scientist or software engineer, so we spend this episode learning about best practices from three experienced Klaviyo engineers.

Listen along to learn more about:

  • How to make sure your code is “battle-ready,” whether you’re working on a data science project or not
  • Why error messages you think are safe to ignore may not actually be safe to ignore
  • One key lesson for safely deploying your code, no matter what environment you work in

“That’s stuck with me through the years: there are these knock-on effects between things. Even if it’s not your code, you should still try to understand how it’s working and whether it can have a ripple effect that comes back and affects your code.”— Chris Conlon, Lead Software Engineer

Check out the full show notes on Medium!

  continue reading

47 episoder

Alla avsnitt

×
 
Loading …

Välkommen till Player FM

Player FM scannar webben för högkvalitativa podcasts för dig att njuta av nu direkt. Den är den bästa podcast-appen och den fungerar med Android, Iphone och webben. Bli medlem för att synka prenumerationer mellan enheter.

 

Snabbguide