Abstract: Techniques are provided for automated item assortment selection using processor-based objective function evaluation of designated goal scores. One method comprises obtaining information characterizing a plurality of items, a performance of the plurality of items and a plurality of designated attainment goals of an organization associated with the plurality of items; applying at least portions of the obtained information to at least one algorithm to obtain data characterizing a selected item assortment comprising a subset of the plurality of items, wherein the at least one algorithm evaluates a plurality of item assortments, each comprising a different assortment of the plurality of items, wherein the selected item assortment is selected using an objective function that evaluates an attainment score for the plurality of designated attainment goals of the organization; and initiating processing steps based on the selected item assortment.

Abstract: Methods, apparatus, and processor-readable storage media for resource-related forecasting using machine learning techniques are provided herein. An example computer-implemented method includes obtaining multiple items of data related to one or more resources associated with an enterprise; correlating at least a portion of the multiple items of data with at least one target variable using one or more correlation techniques; generating one or more forecasts pertaining to the at least one target variable and at least a portion of the one or more resources by processing at least a portion of the correlated data using one or more machine learning techniques; and performing one or more automated actions based at least in part on the one or more forecasts.

Abstract: Methods, apparatus, and processor-readable storage media for resource-related forecasting using machine learning techniques are provided herein. An example computer-implemented method includes obtaining multiple items of data related to one or more resources associated with an enterprise; correlating at least a portion of the multiple items of data with at least one target variable using one or more correlation techniques; generating one or more forecasts pertaining to the at least one target variable and at least a portion of the one or more resources by processing at least a portion of the correlated data using one or more machine learning techniques; and performing one or more automated actions based at least in part on the one or more forecasts.