Recommender Systems

A structured, hands-on learning repository covering recommender systems. Built progressively with theory notes and implementations.

---

Curriculum

1. Foundational Paradigms

1. Content-Based Filtering
2. Collaborative Filtering
3. Hybrid Recommendation
4. Feedback Mechanisms
5. Cold-Start Problem

2. Evaluation

1. Why Evaluation Matters
2. Test Evaluation
3. Binary Relevance Metrics
4. Ranked Retrieval Metrics
5. Beyond Relevance Measures
6. Benchmarks

---

Built as part of a structured self-study curriculum. Each module's README contains full theory notes alongside the code.