How can I audit recommendation systems effectively?

What are the key steps to audit a recommendation system?

To audit a recommendation system, start by defining your objectives, then evaluate data quality, algorithm performance, and user feedback.

How do I assess the data quality for the audit?

Check for completeness, accuracy, and relevance of the data. Look for missing values and outliers that could skew results.

What metrics should I use to evaluate algorithm performance?

Common metrics include precision, recall, F1 score, and user engagement metrics like click-through rate and conversion rate.

Can you suggest tools for conducting these audits?

Sure! Tools like Apache Spark for data processing, and libraries like Scikit-learn for performance evaluation are great options.