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Sisällön tarjoaa Klaviyo Data Science Team. Klaviyo Data Science Team tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
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Klaviyo Data Science Podcast EP 30 | These Are a Few of our Favorite Tools

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Manage episode 349147617 series 3251385
Sisällön tarjoaa Klaviyo Data Science Team. Klaviyo Data Science Team tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

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

Tools of the Trade

We talk a lot on this podcast about the results of data science and software engineering work. We even talk about the process of doing data science and software engineering work. But one thing we haven’t shed much light on, until this month, is: what specific tools help a Data Science team — or any developer or data scientist similarly engaged in building a scalable and intelligent system — actually do their work? We asked several data scientists, machine learning engineers, software engineers, designers, and product managers the same question: what is your favorite tool that helps you do your job? You’ll hear all their answers in this episode, including:

  • Why some well-known tools fully deserve the hype
  • Specialized packages for specialized purposes
  • How to slow down and really force yourself to think about the problem
  • How to avoid analysis paralysis
“I like banging out unstyled web forms as much as the next back-end developer, but when you have the experience of spending all day in a tool, those ‘tiny’ things like icon consistency really pay off.”
— Zac Bentley, Lead Site Reliability Engineer II

Read the full show notes, meet this month's guests, and learn more about Klaviyo in our Medium writeup!

  continue reading

47 jaksoa

Artwork
iconJaa
 
Manage episode 349147617 series 3251385
Sisällön tarjoaa Klaviyo Data Science Team. Klaviyo Data Science Team tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

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

Tools of the Trade

We talk a lot on this podcast about the results of data science and software engineering work. We even talk about the process of doing data science and software engineering work. But one thing we haven’t shed much light on, until this month, is: what specific tools help a Data Science team — or any developer or data scientist similarly engaged in building a scalable and intelligent system — actually do their work? We asked several data scientists, machine learning engineers, software engineers, designers, and product managers the same question: what is your favorite tool that helps you do your job? You’ll hear all their answers in this episode, including:

  • Why some well-known tools fully deserve the hype
  • Specialized packages for specialized purposes
  • How to slow down and really force yourself to think about the problem
  • How to avoid analysis paralysis
“I like banging out unstyled web forms as much as the next back-end developer, but when you have the experience of spending all day in a tool, those ‘tiny’ things like icon consistency really pay off.”
— Zac Bentley, Lead Site Reliability Engineer II

Read the full show notes, meet this month's guests, and learn more about Klaviyo in our Medium writeup!

  continue reading

47 jaksoa

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