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Productionizing ML Models for Online Shopping at Loblaws

Offered By: Toronto Machine Learning Series (TMLS) via YouTube

Tags

Machine Learning Courses Cloud Computing Courses E-commerce Courses Microservices Courses CI/CD Courses A/B Testing Courses Recommendation Systems Courses Multi-Armed Bandits Courses

Course Description

Overview

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Explore the process of productionizing machine learning models for online shopping at Loblaws in this 37-minute conference talk by Xiaoming Zhang, a senior data scientist at Loblaw Digital. Learn about the implementation of ML models as managed microservices through CI pipelines, continuous improvement strategies using online A/B and multi-armed bandit testing, and the technical aspects of leveraging cloud platforms and open-source tools like Seldon Core. Gain insights into personalization and recommendation systems for digital shopping experiences, as well as ML model deployment infrastructure. Benefit from Zhang's diverse background in physics, including geophysics and condensed matter theory, as she shares her expertise in data science and model productionization for the retail industry.

Syllabus

Xiaoming Zhang - Productionizing ML Models at Online Shopping at Loblaws


Taught by

Toronto Machine Learning Series (TMLS)

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