You are viewing content from a past/completed QCon -

Presentation: ML for Question and Answer Understanding @Quora

Track: The Practice & Frontiers of AI

Location: Seacliff ABC

Day of week:

Slides: Download Slides

Level: Advanced

Persona: ML Engineer


Quora's mission is to share and grow the world’s knowledge. On Quora, people ask questions on a wide range of topics and Quora surfaces those questions to people with relevant credentials and experiences so they can respond with an insightful, helpful answer. The more you use Quora—whether it’s to ask a question, answer one, or follow people or topics of interest—the better Quora gets. We’re constantly improving our ability to personalize an experience that’s filled with people, questions, and answers you’ve shown interest in. We achieve this via several machine learning and NLP systems.

In this talk, I will discuss these machine learning and NLP systems in depth. I will explore how we extract intelligence from questions on Quora, including how we do question-topic labeling, how we automatically correct questions with bad spelling and grammar, how we detect duplicate questions, how we learn to rank answers to questions and more. I will explain how the output of these systems supply an important input for the downstream machine learning applications that power Quora. Finally, I will highlight lessons I have learned from applying state-of-the-art machine learning techniques to consumer products at scale.

Speaker: Nikhil Dandekar

Leads NLP @Quora

Nikhil Dandekar is a Senior Engineering Manager at Quora, where he leads the NLP team. He joined Quora from Foursquare, where he led the search ranking team. Prior to that, he worked as an engineer and manager on several teams working on web search (Bing) at Microsoft. His expertise is in applying machine learning to internet-scale products.

Find Nikhil Dandekar at

Similar Talks

Machine Learning on Mobile and Edge Devices With TensorFlow Lite


Developer Advocate for TensorFlow Lite @Google and Co-Author of TinyML

Daniel Situnayake

CI/CD for Machine Learning


Program Manager on the Azure DevOps Engineering Team @Microsoft

Sasha Rosenbaum

ML in the Browser: Interactive Experiences with Tensorflow.js


Research Engineer in Machine Learning @cloudera

Victor Dibia

Machine Learning 101


Data Scientist @IBM

Grishma Jena

ML/AI Panel


Staff Developer Relations Engineer @Google Cloud Platform

Amy Unruh