Abstract: A computer-implemented method of dynamically generating a charger map for electric vehicle (EV) charger locations. The method includes providing one or more parameters for a plurality of target areas to a machine learning (ML) model. The ML model is iteratively trained to identify relationships between the parameters using historical data corresponding to the plurality of target areas. One or more target parameters for a user-specific target area are received along with one or more user-specific weights representing one or more prioritized charging features associated with the user-specific target area. A charger map is generated via the trained ML model for the user-specific target area including one or more locations for EV chargers within the user-specific target area. The charger map is optimized relative to the one or more prioritized charging features.