Distributed model optimizer for content consumption

A model training system, comprising:

• a processing system;
• and
• a memory device coupled to the processing system and including instructions stored thereon that, in response to execution by the processing system, are operable to:
• estimate parameter sets for a topic classification (TC) model;
• distribute the estimated parameter sets to multiple different training nodes for separately training associated TC models;
• receiving model performance values for the trained TC models back from the training nodes, the model performance values each associated with one of the estimated parameter sets;
• and
• use the model performance values and the associated estimated parameter sets to generate additional estimated parameter sets for distributing to the training nodes

A model training system, comprising:

• a processing system;
• and
• a memory device coupled to the processing system and including instructions stored thereon that, in response to execution by the processing system, are operable to:
• access a queue to download an estimated parameter set for a topic classification (TC) model;
• train the TC model using the estimated parameter set;
• calculate a model performance value for the trained TC model, the performance value associated with the estimated parameter set used for training the TC model;
• and
• send the model performance value and the estimated parameter set to a master node for generating an additional estimated parameter set for training the TC models.