Presented by Ishant Nayer, Sr Data Scientist at Instacart
Being a data-driven company, Instacart realizes the power of good quality data. While trying to maximize the efficiency of data consumption by all work streams such as recommendation systems and availability systems, we are trying to make our Catalog the best in the world by delivering precise information to all our end-users including shoppers and consumers.
This session will cover the following areas:
1. How we used data science to auto-detect inconsistencies in the data attributes of millions of items comprising the Catalog, in real-time.
2. How we defined and utilized North Star metrics to optimize data quality of our Catalog
3. Different approaches being used to deliver a great customer experience.
Table of contents
- Title: Improving the Worlds Largest Online Grocery Catalog: A Data Science Story
- Release date: September 2019
- Publisher(s): Data Science Salon
- ISBN: None
You might also like
How Uber uses machine learning and deep learning to forecast business
Andrea Pasqua investigates the merits of using deep learning and other machine learning approaches in the …
How Spotify uses machine learning to personalize the user experience
Understanding user listening behavior is essential for personalizing music listening experiences on Spotify. Mounia Lalmas explains …
Natural language processing using transformer architectures
Whether you need to automatically judge the sentiment of a user review, summarize long documents, translate …
Complete Git Guide: Understand and Master Git and GitHub
Complete with practical activities, this comprehensive Git and GitHub guide will help you understand how Git …