Abstract: A system and method are presented. User metadata defining a set of activities undertaken by a user are received by a processor. The processor determines, based on the set of activities, a skill history for the user. The skill history identifies a first plurality of skills associated with the user. The processor determines a preferred career associated with the user, determines, for the preferred career and by accessing a career skill repository, a second plurality of skills associated with the preferred career, determines a missing skill by comparing the first plurality of skills associated with the user to the second plurality of skills associated with the preferred career to identify the missing skill that is in the second plurality of skills and not in the first plurality of skills and outputs a user interface identifying the missing skill.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.