Abstract: Systems and methods for using machine learning to extract data from electronic communications are disclosed. According to certain aspects, a machine learning model is trained on a set of tasks using a set of training data. An electronic communication indicating a purchase of a product and/or service is processed to generate augmented text that is input into the machine learning model. After analyzing the augmented text, the machine learning model outputs a set of predicted values for a set of defined categories, which an entity may use for various purposes such as to apply digital rewards to user accounts.

Abstract: Systems and methods for using machine learning to extract data from electronic communications are disclosed. According to certain aspects, a machine learning model is trained on a set of tasks using a set of training data. An electronic communication indicating a purchase of a product and/or service is processed to generate augmented text that is input into the machine learning model. After analyzing the augmented text, the machine learning model outputs a set of predicted values for a set of defined categories, which an entity may use for various purposes such as to apply digital rewards to user accounts.

Abstract: There is provided an apparatus for docking a piece of portable equipment, such as a portable computer, with another device, such as a peripheral device. In particular, there are a plurality of different pieces of equipment, essentially similar in function but different in design particulars, such as a manufacturer's line of different portable computer models. The docking apparatus includes a first module which has standard interfaces for peripheral devices, and is designed to couple with one of a set of second modules. Each one of the second modules is customized for a respective one of the pieces of equipment.