Machine learning based techniques for predicting component corrosion likelihood

A system, comprising:

• at least one processor, and
• memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
• receiving data associated with a portion of at least one component, the data describing one or more operating conditions of the portion of the at least one component;
• applying, to the data associated with the portion, at least one machine learning model;
• determining, responsive to the applying of the at least one machine learning model, a likelihood of corrosion specific to the at least one component based at least in part on the one or more operating conditions of the portion;
• and
• outputting, automatically and without user intervention, the likelihood of corrosion specific to the at least one component on a display.