This template demonstrates how to build and deploy forecasting models for retail stores.
Accurate and timely forecast in retail business drives success. It is an essential enabler of supply and inventory planning, product pricing, promotion, and placement. As part of the Azure Machine Learning offering, Microsoft provides a template letting data scientists easily build and deploy a retail forecasting solution. In this document, you will learn how to use and customize the template through a demo use case. The graph below presents the workflow of the template. Each step corresponds to an experiment. The output of one experiment is the input of the next. This template provides you a framework to quickly try out multiple models and pick up the best one to build a web service. ![workflow] [workflow]:https://az712634.vo.msecnd.net/samplesimg/v1/T1/workflow.png