Abstract: A system and a process for provisioning a job through a trained machine-learning dynamic provisioning agent is provided herein. An input vector representing the job having one or more job components may be received. One or more additional data vectors representing additional job data may be obtained. For the one or more job components respectively, one or more action values corresponding to one or more provisioning options may be calculated based on the one or more additional data vectors. For the one or more job components respectively, one or more provisioning options for the respective one or more job components may be selected based on the corresponding one or more action values. The one or more selected provisioning options corresponding to the respective one or more job components may be aggregated. The aggregated selected provisioning options may be provided.

Abstract: A system and a process for provisioning a job through a trained machine-learning dynamic provisioning agent is provided herein. An input vector representing the job having one or more job components may be received. One or more additional data vectors representing additional job data may be obtained. For the one or more job components respectively, one or more action values corresponding to one or more provisioning options may be calculated based on the one or more additional data vectors. For the one or more job components respectively, one or more provisioning options for the respective one or more job components may be selected based on the corresponding one or more action values. The one or more selected provisioning options corresponding to the respective one or more job components may be aggregated. The aggregated selected provisioning options may be provided.

Abstract: A system and a process for provisioning a job through a trained machine-learning dynamic provisioning agent is provided herein. An input vector representing the job having one or more job components may be received. One or more additional data vectors representing additional job data may be obtained. For the one or more job components respectively, one or more action values corresponding to one or more provisioning options may be calculated based on the one or more additional data vectors. For the one or more job components respectively, one or more provisioning options for the respective one or more job components may be selected based on the corresponding one or more action values. The one or more selected provisioning options corresponding to the respective one or more job components may be aggregated. The aggregated selected provisioning options may be provided.

Abstract: A system and process for artificially generating training data for machine-learning is provided herein. One or more input vectors for a machine-learning system may be identified. One or more parameters for the training data based on a domain of the machine-learning system may be retrieved. One or more functions for generating the training data corresponding to the one or more input vectors may be retrieved. One or more data sources may be accessed to retrieve one or more sets of data for building a data foundation for generating the training data. Training data corresponding to the one or more input vectors may be generated based on the one or more parameters and the one or more data foundations. The machine-learning system may be trained via the generated training data obtained from the database.

Abstract: A foot and leg warmer or foot covering configured for wearing by a user, the foot and leg warmer having a sole portion, front portion, rear portion, upper front portion, and an adjustable attachment configured for allowing the user to fit the foot and leg warmer to the user's body. The foot covering configured for attaching above a wearer's calf muscle, thereby using the warmth of the wearer's calf muscle to heat air trapped within the foot covering and thereby heats the wearer's lower extremities.

Abstract: A foot and leg warmer or foot covering configured for wearing by a user, the foot and leg warmer having a sole portion, front portion, rear portion, upper front portion, and an adjustable attachment configured for allowing the user to fit the foot and leg warmer to the user's body. The foot covering configured for attaching above a wearer's calf muscle, thereby using the warmth of the wearer's calf muscle to heat air trapped within the foot covering and thereby heats the wearer's lower extremities.