Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

ETA Prediction with Graph Neural Networks in Google Maps - Paper Explained

Aleksa Gordić - The AI Epiphany via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Dive into a comprehensive video explanation of the paper "ETA Prediction with Graph Neural Networks in Google Maps." Explore how Google Maps utilizes Graph Neural Networks (GNNs) for real-world applications, including graph formation, feature extraction, and the DeepMind GN model. Learn about different prediction horizons, loss functions, variance reduction techniques, and ETA baselines. Understand the inference process, offline results, and various experiments conducted. Gain insights into the engineering aspects of implementing GNNs in production for accurate travel time estimation.

Syllabus

Intro - GNNs in production
How graphs are formed
Graph features
GNN explained DeepMind GN
Different horizons
Loss functions
Reducing the variance
ETA baselines explained
How does the inference work
Offline results
Ablations and experiments
Outro, engineering

Taught by

Aleksa Gordić - The AI Epiphany

Reviews

5.0 rating, based on 1 Class Central review

Start your review of ETA Prediction with Graph Neural Networks in Google Maps - Paper Explained

  • M Nandu
    It's good course to learn in a short time. And the way explain was awesome.Thanks to Google .Neural Networks in Google was it's a good experience for me .also it's using in Google maps

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.