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CodeSignal

Recommendation Systems Quality Evaluation

via CodeSignal

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Overview

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.

Syllabus

  • Unit 1: Understanding and Calculating Coverage in Recommendation Systems
    • Increasing Recommendation Diversity
    • Implement Coverage Function from Scratch
    • Visualize Model Coverage Effectively
    • Calculate Coverage with XGBoost
  • Unit 2: Novelty in Recommendation Systems
    • Boost Your Recommendation Novelty
    • Calculate Novelty for Multiple Users
    • Calculating Average Novelty Scores
    • Calculate Novelty with Item Popularity
  • Unit 3: Diversity in Recommendation Systems
    • Calculate Cosine Similarities Easily
    • Calculate Cosine Similarity Efficiently
    • Calculate Recommendation Diversity Score
    • Decrease Diversity in Recommendations
    • Enhance Dataset for Better Diversity
  • Unit 4: Serendipity Calculation in Recommendation Systems
    • Boost Your Recommendation Skills
    • Complete the Serendipity Function
    • Calculating Serendipity for Multiple Users

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