Researchers at McGill University's Desautels Faculty of Management are exploring the application of machine learning to optimize supply chain operations in Canada, with a focus on reducing costs and improving efficiency.
IBM offers a range of machine learning solutions to help Canadian businesses optimize their supply chains, from demand forecasting to inventory management and logistics optimization.
Statistics Canada explores the potential of machine learning to improve supply chain efficiency in the Canadian context, including case studies and best practices for implementation.
The University of Toronto's Rotman School of Management offers a course on applying machine learning to supply chain management, covering topics such as predictive analytics and optimization techniques.
This academic review article examines the current state of research on machine learning in supply chain management, including applications, methodologies, and future directions.
CBC News profiles a Canadian company that has successfully implemented machine learning to optimize its supply chain, resulting in significant cost savings and improved customer satisfaction.
This online course, offered through Coursera, provides an introduction to machine learning for supply chain optimization, covering topics such as data preprocessing, model selection, and implementation.
Deloitte Canada offers a guide for businesses on how to apply machine learning to optimize their supply chains, including strategies for data collection, model development, and deployment.