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Learn AI with Python · Lesson

Hybrid Systems and Evaluation Metrics

Combining collaborative + content-based, RMSE, MAE, Precision@K, Recall@K.

Why Hybrid Systems?

Collaborative filtering struggles with cold-start; content-based filtering over-specializes. A hybrid system combines them so each method covers the other weaknesses, usually beating either alone.

Weighted Combination

The simplest hybrid blends scores with weights that sum to 1. For example 0.6 * CF + 0.4 * CB leans on collaborative signals but keeps content as a fallback and diversifier.

final_score = 0.6 * cf_score + 0.4 * cb_score

All lessons in this course

  1. Collaborative Filtering: User-Based and Item-Based
  2. Matrix Factorization with SVD
  3. Content-Based Filtering
  4. Hybrid Systems and Evaluation Metrics
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