Adaptive fine-tuning of machine learning models using genetic algorithms

A system for automatically optimizing a machine learning model, comprising:

• one or more processors;
• and
• a memory comprising instructions that, when executed by the one or more processors, cause the system to:
• determine a set of initial configurations for parameters associated with the machine learning model;
• select a configuration based on the set of initial configurations and an evolutionary selection process comprising excluding configurations that result in a level of performance for the machine learning model that is below a threshold;
• and
• execute the machine learning model using the selected configuration.

A non-transitory computer readable medium comprising instructions that, when executed by one or more processors of a computing system, cause the computing system to:

• determine a set of initial configurations for parameters associated with the machine learning model;
• select a configuration based on the set of initial configurations and an evolutionary selection process comprising excluding configurations that result in a level of performance for the machine learning model that is below a threshold;
• and
• execute the machine learning model using the selected configuration.