Update: Video Recording:
After our last 2 meetups with core developers of XGBoost and LightGBM, respectively, it is now CatBoost’s turn (with the head of the CatBoost dev team speaking)! Just as last time, we’ll fit in a 1-hour slot, talk 35 minutes + Q&A 20 minutes (10:00-10:55am Pacific Time).
The zoom link will be posted in comments below at 9:55am and due to our zoom’s 100-attendee limit, the first 100 people will be able to join the zoom call.
CatBoost: Distributed Training, Uncertainty Estimation and Other News
by Stanislav Kirillov
CatBoost is a popular open-source library for training gradient boosting models, with built-in categorical, text, and embedding features support.
In this talk, we will discuss major updates and recall the main features of CatBoost, including:
* CatBoost for Spark release
* Object embeddings and text features support
* Uncertainty estimation
* GPU training support
* Dataset prequantization support
* Fast inference (both CPU and GPU)
We will show a brief demo of CatBoost PySpark training and present plans for CatBoost development.
Stanislav Kirillov is the head of CatBoost development team at Yandex. He develops machine learning tools, supporting and developing infrastructure for them. Stanislav is a big fan of distributed training and low-level software optimizations.
Date/Time: Tuesday, March 30, 10:00-10:55am Pacific Time
Venue: online (zoom)
RSVP: here on meetup
Note: The zoom link will be posted in comments on meetup (link above) at 9:55am and due to our zoom’s 100-attendee limit, the first 100 people will be able to join the zoom call.