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Boosted Trees and Deep Neural Networks for Better Recommender Systems

Offered By: Nvidia via YouTube

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Recommender Systems Courses GPU Acceleration Courses Deep Neural Networks Courses XGBoost Courses Kaggle Courses

Course Description

Overview

Dive into an in-depth exploration of advanced recommender systems in this 1-hour 11-minute video from the Nvidia Grandmaster Series. Learn how Kaggle Grandmasters of NVIDIA (KGMON) leveraged GPU-accelerated boosted trees and deep neural networks to create the winning solution for the ACM RecSys Challenge hosted by Twitter. Discover the intricacies of predicting user engagement probabilities for various tweet interactions using heterogeneous input data. Explore neural network models, target encoding techniques, XGBoost models, and the effective stacking model strategy employed by the winners. Gain valuable insights into building cutting-edge recommendation systems through detailed explanations, practical examples, and expert commentary from industry leaders in data science and AI.

Syllabus

– Intro to Episode Six
– ACM RecSys Challenge Overview
– Neural Network Models
– Target Encoding & XGBoost Models
– Stacking Model Strategy
– Closing Remarks


Taught by

NVIDIA Developer

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