A machine learning (ML) model is a computer program or mathematical algorithm that has been trained on data to identify patterns, make decisions, or generate predictions on new, unseen data. It is the "end product" of running an algorithm on a dataset to learn from experience, rather than following pre-set, explicit instructions.
Models are the reasoning engine of agents. They drive the agent’s decision-making process, determining which tools to call, how to interpret results, and when to provide a final answer.
With agents - Models can be dynamically specified when creating an agent.
Standalone - Models can be called directly (outside of the agent loop) for tasks like text generation, classification, or extraction without the need for an agent framework.
0-2 years experience
5-8 years experience
8+ years experience
