How ML Keeps Shelves Stocked at Home Depot with Pat Woowong - TWiML Talk #175

This article summarizes a podcast episode from Practical AI, focusing on how The Home Depot uses machine learning to manage shelf stock. The guest, Pat Woowong, a principal engineer at Home Depot, discusses a project presented at the Google Cloud Next conference. The project utilizes machine learning to predict when shelves will be out of stock. The article highlights the motivation behind the system, the development process, and the use of Kubernetes for scalability. The focus is on practical applications of machine learning in a retail environment, offering insights into how AI is used to improve operational efficiency and customer experience.

• •Machine learning is used to predict shelf-out scenarios in a retail environment.
• •The project was presented at the Google Cloud Next conference.
• •Kubernetes is used to support future growth of the platform.