Recommender Systems at Etsy: Current Trends and Evolution

Logo
Presented by

Moumita Bhattacharya (Etsy)

About this talk

In this talk, Moumita Bhattacharya, Senior Data Scientist at Etsy, will present an overview of recommender systems, including traditional content based and collaborative filtering. She will touch upon some current trends and breakthroughs in this area and provide an overview of how recommendations are developed at Etsy. Specifically, she will discuss Etsy's journey from linear ranking models to a non-linear deep neural network ranking model, the challenges they faced and the lessons they learnt. Speaker bio: Moumita Bhattacharya is a Senior Data Scientist at Etsy, a two-sided marketplace for buyers and sellers. At Etsy, Moumita is the tech lead of a team that develops recommendation systems to show relevant items to Etsy users. Recently, she developed a ranking method to improve conversion rates and gross merchandise sales of the company. As a part of another project, she developed custom objective functions to optimize for metrics beyond relevance and is also incorporating different contexts in recommendations. Moumita has a PhD in Computer Science with a focus on Machine Learning and its applications in disease prediction and patient risk stratification. Website: https://sites.google.com/udel.edu/moumitabhattacharya

Related topics:

More from this channel

Upcoming talks (3)
On-demand talks (404)
Subscribers (50964)
Dataiku is the world’s leading platform for Everyday AI, systemizing the use of data for exceptional business results. Organizations that use Dataiku elevate their people (whether technical and working in code or on the business side and low- or no-code) to extraordinary, arming them with the ability to make better day-to-day decisions with data. More than 450 companies worldwide use Dataiku to systemize their use of data and AI, driving diverse use cases from fraud detection to customer churn prevention, predictive maintenance to supply chain optimization, and everything in between.