Artificial Intelligence
Recommendation Systems Quality Evaluation
This course focuses on metrics specific to recommendation systems, crucial for evaluating and optimizing model performance. You'll delve into recommendation-specific metrics such as Coverage, Serendipity, Novelty, and Diversity. Each metric is presented with theoretical insights and practical coding examples to illustrate their application.
C++
4 lessons
16 practices
1 hour
Model Validation and Selection
Course details
Coverage in Recommendation Systems
Increase Recommendation Coverage
Implementing the Coverage Metric for Recommendation Systems
Calculating and Displaying Model Coverage
Calculating Recommendation Coverage in a Model-Based System
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