Klaviyo Data Science Podcast

Klaviyo Data Science Podcast EP 15 | Books every data scientist should read (vol. 2)

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

(More) required reading for data science

A question we frequently get asked is: what books should I read to be a better data scientist/machine learning engineer? This may not surprise you, but there isn’t just one answer — in fact, we spent an entire episode talking about three ways to level up your data science knowledge and skills. This month, we’re back with three more:

  • One of the foremost foundational texts for understanding machine learning models in a statistical way
  • A survey course for a broad variety of machine learning models, with the opportunity to go in depth on topics like deep learning
  • A foundational text in designing and analyzing experiments — both in ideal scenarios and in cases where the standard assumptions aren’t met
    • Mentioned this episode

    We discuss the following books and courses in this episode:

    • The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani, and Jerome Friedman: https://web.stanford.edu/~hastie/ElemStatLearn/
    • Kirill Eremenko’s A-Z courses on data science, machine learning, artificial intelligence, and deep learning
    • Field Experiments: Design, Analysis, and Interpretation by Alan Gerber and Donald Green: https://wwnorton.com/books/9780393979954
      • About Klaviyo

      Klaviyo helps growth-focused ecommerce brands drive more sales with super-targeted, highly relevant email, Facebook, and Instagram marketing. Interested? We’re always looking for great people to join our team.

      Who’s who
      • Michael Lawson, Senior Data Scientist
      • Nuvan Rathnayaka, Statistician at NoviSci
      • Chad Furman, Senior Software Engineer
      • David Lustig, Data Scientist

        • Edited by: Michael Lawson

        Logo by: Griffin Drigotas, Ally Hangartner from Klaviyo Design

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        Klaviyo Data Science PodcastBy Klaviyo Data Science Team
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