O'Reilly logo
live online training icon Live Online training

Spotlight on Data: Improving Uber’s Customer Support with Natural Language Processing and Deep Learning with Piero Molino

An interactive case study from Uber

Piero Molino

Watch the video recording of this event.

For a company looking to provide delightful user experiences, it's critical to resolve customer issues quickly and efficiently. Uber has implemented COTA, a system that helps representatives provide the best experience to customers by suggesting the best solutions. COTA improves the speed and reliability of customer support through automated ticket classification and answer selection for support representatives. By improving speed and reliability, COTA also helps reduce customer support operations costs.

Join us for this edition of Spotlight on Data to find out how Uber leverages large-scale data and deep learning models for operational efficiency and improved user experience. Piero Molino will detail how Uber has reduced issue resolution time by 20% while maintaining levels of customer satisfaction, using NLP, deep learning, A/B testing, and productionized models.

O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. You’ll engage in a live conversation with experts, sharing your questions and ideas while hearing their unique perspectives, insights, fears, and predictions for the future.

In every edition of Spotlight on Data, you’ll learn about, discuss, and debate the tools, techniques, questions, and quandaries in the world of data. You’ll discover how successful companies leverage data effectively and how you can follow their lead to transform your organization and prepare for the Next Economy.

What you'll learn-and how you can apply it

By the end of this live show, you’ll better understand:

  • How Uber uses NLP and ML to reduce ticket-handling time without impacting customer satisfaction, reducing costs as a consequence
  • The best models for putting such a system in place, how to put those models into production, and the pitfalls to avoid when doing so

This training course is for you because...

  • You're an engineer, product manager, research scientist, or entrepreneur who wants to put ML and NLP systems in production.
  • You want to learn how other companies have approached similar challenges.

Prerequisites

  • Come with your questions for Piero Molino
  • Have a pen and paper handy to capture notes, insights, and inspiration

Recommended follow-up:

About your instructor

  • Piero Molino is a senior research scientist at Uber AI, where he focuses on machine learning for language and dialogue. Previously, he founded QuestionCube, a startup that built a framework for semantic search and QA, and worked on learning to rank at Yahoo Labs in Barcelona, on natural language processing with deep learning at IBM Watson in New York, and on grounded language understanding at Geometric Intelligence (acquired by Uber). Piero holds a PhD on question answering from the University of Bari, Italy.

Schedule

The timeframes are only estimates and may vary according to how the class is progressing

Tuesday, July 2, 2019, at 9:00am PT / 12:00pm ET

  • Introduction and presentation (15 minutes)
  • Interactive discussion and Q&A (45 minutes)