Precision and recall are fundamental metrics that are used to measure the performance of classifiers, particularly in binary classification tasks and information retrieval. Both metrics measure the model's ability to identify relevant results but they are focused on different aspects. Data scientists, machine-learning engineers, and anyone who works with classification systems must understand the differences between these metrics. Data Science Course in Pune