Accuracy Metrics

Accuracy metrics are quantifiable measures used to evaluate the performance of machine learning models, algorithms, and statistical predictions by comparing their outputs to actual outcomes. By using accuracy metrics, developers and data scientists can assess the reliability and effectiveness of their models, identify areas for improvement, and optimize their performance, making them a crucial tool in the tech community for building and refining AI and data-driven applications.