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Practical Data Science with Rafal Lukawiecki

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Manage episode 175708211 series 19264
Content provided by Richard Campbell. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Richard Campbell or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

How do you get started in data science? Richard chats with long time data scientist Rafal Lukawiecki about practical data science. Rafal starts out focusing on the most common data science scenarios - understanding your customer and their needs. This goal is more complicated than it appears, often the questions first asked are not the questions you'll actually need answers to. But asking them is important since it leads to information that will influence the next round of questions. The cloud has made it easier than ever to dive into data science, but the principals are still the same: This is a science, after all!

  continue reading

983 episodes

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Practical Data Science with Rafal Lukawiecki

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Manage episode 175708211 series 19264
Content provided by Richard Campbell. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Richard Campbell or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

How do you get started in data science? Richard chats with long time data scientist Rafal Lukawiecki about practical data science. Rafal starts out focusing on the most common data science scenarios - understanding your customer and their needs. This goal is more complicated than it appears, often the questions first asked are not the questions you'll actually need answers to. But asking them is important since it leads to information that will influence the next round of questions. The cloud has made it easier than ever to dive into data science, but the principals are still the same: This is a science, after all!

  continue reading

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