Machine learning platform

A non-transitory computer readable medium storing a plurality of instructions executable by one or more processors, wherein the plurality of instructions, when executed by the one or more processors, causes the one or more processors to perform processing comprising:

• selecting a model group and a model selector for the model group, wherein:
• the model group includes one or more machine learning (ML) models, each ML model in the model group configured to perform a same function;
• and
• the model selector is configured to dynamically select, based on a set of rules or a trainable selection model, at least one ML model from the model group for data analysis;
• analyzing input data using the model group and the model selector;
• determining, during the analyzing, a score for the model group and the model selector based on the analyzing and a set of scoring metrics;
• and
• updating, during the analyzing, the model selector or the model group based upon determining that the score is below a threshold value.

A system comprising:

• one or more processors;
• and
• a memory coupled to the one or more processors, the memory storing instructions, which, when executed by the one or more processors, cause the system to:
• select a model group and a model selector for the model group, wherein:
• the model group includes one or more machine learning (ML) models, each ML model in the model group configured to perform a same function;
• and
• the model selector is configured to dynamically select, based on a set of rules or a trainable selection model, at least one ML model from the model group for data analysis;
• analyze input data using the model group and the model selector;
• determine, during the analyzing, a score for the model group and the model selector based on the analyzing and a set of scoring metrics;
• and
• update, during the analyzing, the model selector or the model group based upon determining that the score is below a threshold value.