694: CatBoost: Powerful, efficient ML for large tabular datasets

episode

Super Data Science: ML & AI Podcast with Jon Krohn not yet transcribed

▲ 0

Transcript

This episode hasn't been transcribed yet Upvotes decide what gets transcribed next — 0 so far. Sign in to upvote

Related

recent transcribed audio

Transrapid, Flugtaxis, Hyperloop – Warum es neuartige Verkehrstechnik so schwer hat 28 min · 22 Sep 2026 · Das Wissen | SWR

Las 10 de Erazno, el Chokolatazo, Parodias, Nacadas y mas 1h 25m · 22 Sep 2026 · Erazno y La Chokolata El Podcast

Cross-code immorality, Lachie Neale's strike, crowd behaviour - Andrew Voss | Across the Divide! (22.09.26) 17 min · 22 Sep 2026 · Whateley

S13 EP19: It's Exhausting Having an Opinion 37 min · 22 Sep 2026 · Parenting Hell with Rob Beckett and Josh Widdicombe

Fall in Love With the Life You Have 51 min · 22 Sep 2026 · The Candace Cameron Bure Podcast

NPR News: 09-21-2026 9PM EDT 5 min · 22 Sep 2026 · NPR News Now

Report any issue

Source

Recorded07 Jul 2023

Publisherfeeds.megaphone.fm

Handlerec:6202692

Show notes

Modeling tabular data and spreadsheets doesn’t have to be tedious with CatBoost’s open-source tree-boosting algorithm. CatBoost does what it says on the tin, blending categories with boosting that allows you to train your models faster and handle large datasets for ML tasks across multiple GPUs. In this week’s Five-Minute Friday, host Jon Krohn gets to grips with the technical components of CatBoost that give it the speed and accuracy so acclaimed by its users.Additional materials: www.superdatascience.com/694Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Ask this episode

“What did the council decide on item 42?” — answered with the speaker and the moment.

Sign in