How Machine Learning Helps Levi’s Leverage Data to Enhance E-Commerce Experience

Levi Strauss & Co. (Levi’s) had already migrated its store and data science applications to the cloud. It needed a way to quickly create prototypes and put them into production to create different meaningful customer experiences on the website. Levi’s used Dataiku Data Science Studio (DSS) and Amazon Web Services (AWS) to create a recommendation system that aligns to a customer journey, such as showing best-selling products in their region to new customers or displaying complementary items to complete an outfit to returning purchasing customers. Watch this webinar to learn how machine learning enables Levi’s to easily and quickly leverage its data to create new products for its customers. Watch to learn how to: - Try different algorithms and ways of connecting data together through data pipelines to move beyond experimentation into operations - Use Amazon SageMaker for model training - Create prototypes in Dataiku DSS and use AWS to put them into production - Run multiple processes in parallel