Abstract: Aspects of the disclosure relate to systems, methods, and computing devices for managing the processing and execution of machine learning classifiers across a variety of platforms. Machine classifiers can be developed to process a variety of input datasets. In several embodiments, a variety of transformations can be performed on raw data to generate the input datasets. The raw data can be obtained from a disparate set of data sources each having its own data format. The generated input datasets can be formatted using a common data format and/or a data format specific for a particular machine learning classifier. A sequence of machine learning classifiers to be executed can be determined and the machine learning classifiers can be executed on one or more computing devices to process the input datasets. The execution of the machine learning classifiers can be monitored and notifications can be transmitted to various computing devices.

Abstract: Aspects of the disclosure relate to systems, methods, and computing devices for managing the processing and execution of machine learning classifiers across a variety of platforms. Machine classifiers can be developed to process a variety of input datasets. In several embodiments, a variety of transformations can be performed on raw data to generate the input datasets. The raw data can be obtained from a disparate set of data sources each having its own data format. The generated input datasets can be formatted using a common data format and/or a data format specific for a particular machine learning classifier. A sequence of machine learning classifiers to be executed can be determined and the machine learning classifiers can be executed on one or more computing devices to process the input datasets. The execution of the machine learning classifiers can be monitored and notifications can be transmitted to various computing devices.