Klaviyo Data Science Podcast EP 34 | Books every data scientist should read (vol. 3)

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

Back by popular demand: data science is a broad, deep field with an extraordinary amount to learn, and we’re here to help you learn it. We asked four members of the Data Science team at Klaviyo what one of their favorite data science books was, and we got four different answers. Listen on if you’ve wanted to know more ways to learn about:

• How to think about and employ the Bayesian framework (and corgis)
• Learning intro-to-intermediate coding skills necessary for data science work
• The theory that drives natural language processing
• The mindset of a data scientist in general

“it gives you a different lens to apply to different problems. And sometimes taking that different lens, suddenly a problem that was really hard to formulate using traditional frequentist statistics or machine learning techniques, suddenly it can be really easy to frame in this other way” - Tommy Blanchard, Senior Data Science Manager

Read the full writeup on Medium!