Choose this use-case if you wish to develop a model that analyzes historical sales data and attributes for a product or service to predict future sales. Given a dataset containing historical sales data and an optional secondary dataset of item attributes (e.g. item type, specifications, availability, or reviews) you can generate a model that forecasts sales.
Dataset and Feature Group RequirementsThis section specifies the Datasets / Feature Groups requirements to successfully train a Sales and Revenue Forecasting model. Feature requirements include recommendations on additional datasets that might enhance model performance.
Training Models - Training Options and MetricsThis section describes all the available model training options that can be used to create a Sales and Revenue Forecasting model. You can utilize the metric explanations to better understand how they measure the performance of the model you trained.
Evaluating PredictionsThis section contains a quick model evaluation guide that helps you understand how well your model is performing.
Prediction APIThis section discusses the prediction API method so that you could properly generate predictions from the model you deployed.