Abstract: An exercise recommendation system determines workout plans for users. The exercise recommendation system receives a profile of a user and a level of variance selected by the user. The profile includes a history of exercises the user has performed, available gym equipment, and exercise goals. The exercise recommendation system inputs the profile to a machine learning model configured to rank a set of exercises for a user to perform. The exercise recommendation system modifies the ranking of exercises based on the level of variance selected by the user. Modification of the ranking is greater for a first level of variance than for a second level of variance less than the first level of variance. The exercise recommendation system generates a workout plan for display within a user interface to the user based on the modified ranking.

Abstract: An exercise recommendation system determines a current capability of a user. The exercise recommendation system accesses an exercise history for a user. The exercise history comprises an exercise performed by the user and a capability of the user each time the user performed the exercise. The exercise recommendation system partitions the exercise history into a plurality of time periods, and, for each time period, computes an aggregate capability of the user for the exercise during the time period. The exercise recommendation system calculates a moving average capability of the user for the exercise based on the aggregate capabilities and determines a current capability of the user for the exercise based on the moving average capability. The current capability of the user may be discounted at least in part based on how recently the user performed the exercise.

Abstract: An exercise recommendation system determines a current capability of a user. The exercise recommendation system accesses an exercise history for a user. The exercise history comprises an exercise performed by the user and a capability of the user each time the user performed the exercise. The exercise recommendation system partitions the exercise history into a plurality of time periods, and, for each time period, computes an aggregate capability of the user for the exercise during the time period. The exercise recommendation system calculates a moving average capability of the user for the exercise based on the aggregate capabilities and determines a current capability of the user for the exercise based on the moving average capability. The current capability of the user may be discounted at least in part based on how recently the user performed the exercise.

Abstract: An exercise recommendation system determines workout plans for users. The exercise recommendation system receives a profile of a user and a level of variance selected by the user. The profile includes a history of exercises the user has performed, available gym equipment, and exercise goals. The exercise recommendation system inputs the profile to a machine learning model configured to rank a set of exercises for a user to perform. The exercise recommendation system modifies the ranking of exercises based on the level of variance selected by the user. Modification of the ranking is greater for a first level of variance than for a second level of variance less than the first level of variance. The exercise recommendation system generates a workout plan for display within a user interface to the user based on the modified ranking.

Abstract: An exercise recommendation system determines a current capability of a user. The exercise recommendation system accesses an exercise history for a user. The exercise history comprises an exercise performed by the user and a capability of the user each time the user performed the exercise. The exercise recommendation system partitions the exercise history into a plurality of time periods, and, for each time period, computes an aggregate capability of the user for the exercise during the time period. The exercise recommendation system calculates a moving average capability of the user for the exercise based on the aggregate capabilities and determines a current capability of the user for the exercise based on the moving average capability. The current capability of the user may be discounted at least in part based on how recently the user performed the exercise.

Abstract: An exercise recommendation system determines recommended weights for users to perform exercises with. The exercise recommendation system accesses a plurality of exercise pairs, each labeled with performance statistics of users who performed the exercises. Each exercise in an exercise pair is associated with a weight. The exercise recommendation system trains a machine learning model on the plurality of exercise pairs to determine a weight to recommend to a user for a first exercise based on performance statistics of the user associated with one or more second exercises, which are each in an exercise pair with the first exercise. The exercise recommendation system retrieves performance statistics of a target user including weights for exercises previously performed by the target user. The exercise recommendation system applies the machine learning model to the performance statistics to determine a target weight to recommend and modifies a user interface to include the target weight.

Abstract: A device, system, and method may include a network interface device communicatively coupled to a user interface. The device, system, and method may further include a processor, coupled to the network interface device, configured to cause the user interface to display a content display area, the content display area configured to display a of pages. At least one of the pages is displayed based on a user selection and at least one of the pages being displayed without respect to a user selection. The of pages form a stack with respect to one another, a newly selected one of the of pages being displayed on a top of the stack and an oldest-selected one of the of pages being displayed on a bottom of the stack, ones of the of pages not on the top of the stack being displayed only in part.

Abstract: A device, system, and method may variously include or utilize a processor to cause a user device to display a content selection display area and a content display area. The content selection display area may include subject matter categories and icons, at least some of the icons being individually associated with at least one of the subject matter categories and at least some of the categories being associated with at least one of the plurality of icons. Each category is associated with at most a predetermined number of the plurality of icons. The content display area is configured to display content corresponding to at least one of the plurality of icons as selected in the content selection display area.

Abstract: A device, system, and method may variously include a network interface device communicatively coupled to a user interface and a processor, coupled to the network interface device, configured to cause the user interface to display a newsfeed including social network content items, the newsfeed being configured to scroll to display ones of the social network content items on the user interface. At least one of the content items includes a title and content. The content item is configurable in an expanded state corresponding to displaying all of the content of the content item upon a user selection and a contracted state corresponding to displaying a sub-portion of the content. The newsfeed is configured to display the content items in the contracted state upon the social network content item scrolling onto the user interface without respect to the content item being in an expanded state when previously displayed.

Abstract: A device, system, and method may variously include or utilize a processor to cause a user device to display a content selection display area and a content display area. The content selection display area may include subject matter categories and icons, at least some of the icons being individually associated with at least one of the subject matter categories and at least some of the categories being associated with at least one of the plurality of icons. Each category is associated with at most a predetermined number of the plurality of icons. The content display area is configured to display content corresponding to at least one of the plurality of icons as selected in the content selection display area.

Abstract: A device, system, and method may include a network interface device communicatively coupled to a user interface. The device, system, and method may further include a processor, coupled to the network interface device, configured to cause the user interface to display a content display area, the content display area configured to display a of pages. At least one of the pages is displayed based on a user selection and at least one of the pages being displayed without respect to a user selection.

Abstract: A device, system, and method may variously include a network interface device communicatively coupled to a user interface and a processor, coupled to the network interface device, configured to cause the user interface to display a newsfeed including social network content items, the newsfeed being configured to scroll to display ones of the social network content items on the user interface. At least one of the content items includes a title and content. The content item is configurable in an expanded state corresponding to displaying all of the content of the content item upon a user selection and a contracted state corresponding to displaying a sub-portion of the content. The newsfeed is configured to display the content items in the contracted state upon the social network content item scrolling onto the user interface without respect to the content item being in an expanded state when previously displayed.

Abstract: A device, system, and method optionally includes a network interface device communicatively coupled to a user interface and a processor, coupled to the network interface device, configured to generate and cause the user interface to display an icon, the icon including a graphic and a background based, at least in part, on a blurred form of the graphic and an overlay color.