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Episode 17: End-to-End Data Science

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Manage episode 355618614 series 3317544
Content provided by Hugo Bowne-Anderson. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Hugo Bowne-Anderson 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.

Hugo speaks with Tanya Cashorali, a data scientist and consultant that helps businesses get the most out of data, about what end-to-end data science looks like across many industries, such as retail, defense, biotech, and sports, including

  • scoping out projects,
  • figuring out the correct questions to ask,
  • how projects can change,
  • delivering on the promise,
  • the importance of rapid prototyping,
  • what it means to put models in production, and
  • how to measure success.

And much more, all the while grounding their conversation in real-world examples from data science, business, and life.

In a world where most organizations think they need AI and yet 10-15% of data science actually involves model building, it’s time to get real about how data science and machine learning actually deliver value!

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  continue reading

32 episodes

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Episode 17: End-to-End Data Science

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Manage episode 355618614 series 3317544
Content provided by Hugo Bowne-Anderson. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Hugo Bowne-Anderson 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.

Hugo speaks with Tanya Cashorali, a data scientist and consultant that helps businesses get the most out of data, about what end-to-end data science looks like across many industries, such as retail, defense, biotech, and sports, including

  • scoping out projects,
  • figuring out the correct questions to ask,
  • how projects can change,
  • delivering on the promise,
  • the importance of rapid prototyping,
  • what it means to put models in production, and
  • how to measure success.

And much more, all the while grounding their conversation in real-world examples from data science, business, and life.

In a world where most organizations think they need AI and yet 10-15% of data science actually involves model building, it’s time to get real about how data science and machine learning actually deliver value!

LINKS

  continue reading

32 episodes

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