How do machine learning models work?

Machine learning models work by training algorithms to learn patterns and relationships in large amounts of data. This process involves feeding data into the chosen algorithm, allowing it to identify patterns and features in the data that can be used to make predictions or classifications on new data inputs. The models then leverage these learned patterns to make increasingly accurate predictions over time, as the algorithm continues to learn from new data inputs. This process is iterative, with the model constantly adjusting and refining its predictions based on new data inputs and feedback from human analysts. Ultimately, the goal of a machine learning model is to make accurate predictions or classifications with a high degree of confidence, allowing businesses to make informed decisions based on data-driven insights.

This mind map was published on 16 May 2023 and has been viewed 74 times.