Demand Forecasting Using Automatic Machine-Learning Model Selection

Disclosed is a system for forecasting demand for goods and/or services. In at least certain embodiments the system is configurable to select a machine learning model from among multiple different machine learning models for forecasting demand for a dataset that may be continually being updated over time. The models available to the system are each based on different machine learning algorithms (e.g., linear regression, gradient boosting, neural network, etc.) as well as several variations for each algorithm available to the system. The system can monitor changes in the datasets, changes in accuracy of the machine learning results, and external factors, and based thereon, determine whether to initiate a model reselection process or a model retraining process. Each machine learning model can be evaluated against each dataset and can select the best model for the dataset.