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Klaviyo Data Science Podcast EP 43 | 2023: A Data Science Year in Review

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内容由Klaviyo Data Science Team提供。所有播客内容(包括剧集、图形和播客描述)均由 Klaviyo Data Science Team 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

2023 Year in Review

As the new year starts, we take a look back at 2023. We spoke to 11 data scientist and people who work closely with data scientists, and we asked them all the question we ask every year: what is the coolest data science thing you learned about in 2023? You’ll hear a wide range of answers, including:

  • How data science moving to peripheral devices and becoming more accessible has huge implications for the future of the field
  • Peculiarities of working with large language models, both in terms of the tasks they can carry out and how the process of working with them is more complicated than it seems at first
  • How powerful simple techniques can be at even highly complex tasks

“You don’t have to have a PhD any longer to do data science. And I think that’s amazing and powerful, and it’s going to mean that the future is… where everybody is allowed to do data science stuff without having lots and lots of education.”

 — Wayne Coburn, Director, Product Management

For the full show notes, including stories mentioned in the episode and who's who, see the ⁠⁠⁠Medium writeup⁠⁠⁠.

  continue reading

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Manage episode 395704421 series 3251385
内容由Klaviyo Data Science Team提供。所有播客内容(包括剧集、图形和播客描述)均由 Klaviyo Data Science Team 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

2023 Year in Review

As the new year starts, we take a look back at 2023. We spoke to 11 data scientist and people who work closely with data scientists, and we asked them all the question we ask every year: what is the coolest data science thing you learned about in 2023? You’ll hear a wide range of answers, including:

  • How data science moving to peripheral devices and becoming more accessible has huge implications for the future of the field
  • Peculiarities of working with large language models, both in terms of the tasks they can carry out and how the process of working with them is more complicated than it seems at first
  • How powerful simple techniques can be at even highly complex tasks

“You don’t have to have a PhD any longer to do data science. And I think that’s amazing and powerful, and it’s going to mean that the future is… where everybody is allowed to do data science stuff without having lots and lots of education.”

 — Wayne Coburn, Director, Product Management

For the full show notes, including stories mentioned in the episode and who's who, see the ⁠⁠⁠Medium writeup⁠⁠⁠.

  continue reading

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