Abstract: Techniques for monitoring network connectivity using machine learning are provided. A plurality of historical connectivity records is received, and a first machine learning model type, of a plurality of machine learning model types, is selected based on the plurality of historical connectivity records. A machine learning model, of the first machine learning model type, is trained based on the plurality of historical connectivity records, where the machine learning model learns to generate forecasted connectivity records based on the training.

Abstract: An electric cooking appliance comprises a base frame having a front and rear and left and right sides connecting the front and rear. A generally planar, electrically heated cooking surface is supported by the base frame and has a front and rear edge and a pair of sides connecting the front and rear edges. A splash guard is removably or secured to and extends upwardly from the rear edge and a portion of each of the sides of the cooking surface. A recess or groove is formed in the cooking surface to collect excess cooking oil; and an oil reservoir is carried by the base frame and in fluid communication with the recess in the cooking surface to collect cooking oil from the recess.

Abstract: An electric cooking appliance comprises a base frame having a front and rear and left and right sides connecting the front and rear. A generally planar, electrically heated cooking surface is supported by the base frame and has a front and rear edge and a pair of sides connecting the front and rear edges. A splash guard is removably or secured to and extends upwardly from the rear edge and a portion of each of the sides of the cooking surface. A recess or groove is formed in the cooking surface to collect excess cooking oil; and an oil reservoir is carried by the base frame and in fluid communication with the recess in the cooking surface to collect cooking oil from the recess.