| CPC G06Q 10/0637 (2013.01) [G06F 18/2431 (2023.01)] | 18 Claims |
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1. A system for generating an action strategy, wherein the system comprises:
at least a processor; and
a memory communicatively connected to the processor, the memory containing instructions configuring the at least a processor to:
receive composition data from a user, wherein the composition data comprises:
at least a plurality of pecuniary goals; and
at least a non-goal group comprising data not related to the at least a plurality of pecuniary goals;
train a group classifier using group training data, and wherein training the group classifier further comprises:
correlating the at least a plurality of pecuniary goals of the composition data one or more composition groups;
updating the group training data with a previous correlation of the at least a plurality of pecuniary goals of the composition data to the one or more composition groups; and
retraining the group classifier as a function of the updated group training data, wherein the group classifier is further configured to classify composition data into the one or more composition groups as a function of the at least a plurality of pecuniary goals;
classify the composition data to one or more composition groups using the group classifier;
receive input on the one or more composition groups from an advisor comprising a professional related to a specific composition group;
provide a composition course as a function of the one or more composition groups, wherein providing the composition course comprises training a course machine-learning model on a course training dataset comprising a correlation between at least one example composition group and at least one example composition course, wherein the course machine-learning model comprises at least an artificial neural network comprising an input layer of nodes, one or more intermediate layers of nodes, and an output layer of nodes adjusting one or more connections and one or more weights between nodes in adjacent layers of the course machine-learning model;
receiving additional course training data from the advisor; and
retraining the course machine-learning model as a function of the course training dataset;
determine an action item as a function of the one or more composition groups wherein determining an action item further comprises generating at least an advisor action related to a review with the advisor; and
generate an action strategy comprising at least a tax strategy as a function of the action item comprising a plurality of steps for the action strategy as a function of a focus level, wherein the focus level comprises a user goal, of the one or more composition groups.
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