CPC G06Q 30/0631 (2013.01) [G06F 16/9535 (2019.01); G06Q 30/0627 (2013.01); G06Q 30/0643 (2013.01)] | 20 Claims |
1. A computer-implemented method comprising:
receiving, by a machine learning model, first training data comprising ground truth outfit data, the ground truth outfit data comprising first fashion item data and second fashion item data;
inputting a first visual feature vector representing the first fashion item data into the machine learning model;
generating, by the machine learning model using the first visual feature vector, a first predicted visual feature vector for the second fashion item data;
generating an updated machine learning model by decreasing a difference between the first predicted visual feature vector and a ground truth visual feature vector associated with the second fashion item data;
causing a first graphical user interface (GUI) to be displayed, the first GUI depicting at least a first fashion item image associated with a first category;
determining a first user profile;
determining first filter settings of the first user profile;
receiving a first selection of a first graphical control on the first GUI, the first selection corresponding to a request for a recommendation from a second category;
determining a second fashion item image from among a plurality of fashion item images of the second category, wherein the second fashion item image has been determined by the updated machine learning model based at least in part on a second predicted visual feature vector generated by the updated machine learning model using a visual feature vector for the first fashion item image, and wherein the second fashion item image is selected in accordance with the first filter settings of the first user profile; and
causing the second fashion item image to be displayed on the first GUI.
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