Performance controller for machine learning based digital assistant

A computer-implemented method, comprising:

• training, based at least on a first data, a machine learning model to perform one or more natural language processing tasks;
• deploying, to a production environment, the trained machine learning model to support natural language based interactions with a digital assistant;
• generating a plurality of performance metrics to include explanation data associated with the deployed machine learning model operating on a second data, the explanation data being generated by applying a plurality of explanation models and ensembling an output of each of the plurality of explanation models;
• and
• generating a user interface to display, at a client device, a visual representation of at least a portion of the plurality of performance metrics associated with the deployed machine learning model.

A non-transitory computer readable medium storing instructions, which when executed by at least one data processor, result in operations comprising:

• training, based at least on a first data, a machine learning model to perform one or more natural language processing tasks;
• deploying, to a production environment, the trained machine learning model to support natural language based interactions with a digital assistant;
• generating a plurality of performance metrics to include explanation data associated with the deployed machine learning model operating on a second data, the explanation data being generated by applying a plurality of explanation models and ensembling an output of each of the plurality of explanation models;
• and
• generating a user interface to display, at a client device, a visual representation of at least a portion of the plurality of performance metrics associated with the deployed machine learning model.