Abstract: A first set of performance information pertaining to a previous performance of a first exercise movement is received, the first set of performance information comprising a first weight, a first velocity, and a first range of motion. Target parameters for a target exercise movement based at least in part on the first set of performance information is predicted, wherein the target exercise movement is different from the first exercise movement. An exercise machine is configured to facilitate performing of the target exercise movement based at least in part on the predicted target parameters.

Abstract: A first video of a first individual performing an exercise movement is received, wherein the first video is associated with a first guidance label. A modified version of a video is generated at least in part by passing the first video to a pose data change model. The modified version of the video is associated with a second guidance label. A guidance classifier model is trained using the modified version of the video.

Abstract: A first output is received from a first hardware optical sensor. A second output is received from a second hardware sensor. Guidance is provided for a movement via a user interface, wherein the guidance is based at least in part on: the first output from the first hardware optical sensor; the second output from the second hardware sensor; and a model based at least in part on historical performance of the movement; and wherein at least one of the first output and the second output triggers a condition.