Search a title or topic

Over 20 million podcasts, powered by 

Player FM logo
Artwork

Content provided by Klaviyo Data Science Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Klaviyo Data Science Team 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://staging.podcastplayer.com/legal.
Player FM - Podcast App
Go offline with the Player FM app!

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

44:19
 
Share
 

Manage episode 361634369 series 3251385
Content provided by Klaviyo Data Science Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Klaviyo Data Science Team 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://staging.podcastplayer.com/legal.

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!

  continue reading

58 episodes

Artwork
iconShare
 
Manage episode 361634369 series 3251385
Content provided by Klaviyo Data Science Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Klaviyo Data Science Team 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://staging.podcastplayer.com/legal.

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!

  continue reading

58 episodes

All episodes

×
 
Loading …

Welcome to Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Listen to this show while you explore
Play