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Klaviyo Data Science Team에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Klaviyo Data Science Team 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Klaviyo Data Science Podcast EP 30 | These Are a Few of our Favorite Tools

51:39
 
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Manage episode 349147617 series 3251385
Klaviyo Data Science Team에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Klaviyo Data Science Team 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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

62 에피소드

Artwork
icon공유
 
Manage episode 349147617 series 3251385
Klaviyo Data Science Team에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Klaviyo Data Science Team 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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

62 에피소드

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