Put AI to Work
April 15-18, 2019
New York, NY
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ML at Twitter: A deep dive into Twitter's timeline

Cibele Halasz (Apple), Satanjeev Banerjee (Twitter)
1:00pm1:40pm Wednesday, April 17, 2019
Case Studies, Machine Learning
Location: Sutton South
Secondary topics:  AI case studies, Media, Marketing, Advertising, Platforms and infrastructure, Text, Language, and Speech
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

  • Machine learning engineers, software engineers, and researchers



Prerequisite knowledge

  • Familiarity with machine learning (architectures, hyperparameter tuning, etc.) and TensorFlow

What you'll learn

  • Understand how to implement ML at production scale
  • Explore an ML pipeline at Twitter
  • Discover optimizations for sparse workloads the team made inside of TensorFlow


Machine learning has allowed Twitter to drive engagement, promote healthier conversations, and deliver catered advertisements. Cibele Montez Halasz and Satanjeev Banerjee describe one of those use cases: timeline ranking. They share some of the optimizations that the team has made—from modeling to infrastructure—in order to have models that are both expressive and efficient. You’ll explore the feature pipeline, modeling decisions, platform improvements, hyperparameter tuning, and architecture (alongside discretization and isotonic calibration) as well as some of the challenges Twitter faced by working with heavily text-based (sparse) data and some of the improvements the team made in its TensorFlow-based platform to deal with these use cases. Join in to gain a holistic view of one of Twitter’s most prominent machine learning use cases.

Cibele Halasz


Satanjeev Banerjee