Implement CLI-first music recommender with scoring, ranking, and expl… - #29
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danielled101 wants to merge 3 commits into
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Implement CLI-first music recommender with scoring, ranking, and expl…#29danielled101 wants to merge 3 commits into
danielled101 wants to merge 3 commits into
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…anations Add a working CLI-first simulation: load_songs parses data/songs.csv into typed dicts, score_song/_score_components apply the Algorithm Recipe (genre +2.0, mood +1.0, energy closeness up to +1.0, acousticness +0.5), and recommend_songs ranks the full catalog to return the top k with human-readable reasons. The OOP Recommender class shares the same scoring logic for the dataclass-based API used by tests. main.py prints a readable ranked report, and README documents the data flow, recipe, and sample output. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Add a working CLI-first simulation: load_songs parses data/songs.csv into typed dicts, score_song/_score_components apply the Algorithm Recipe (genre +2.0, mood +1.0, energy closeness up to +1.0, acousticness +0.5), and recommend_songs ranks the full catalog to return the top k with human-readable reasons. The OOP Recommender class shares the same scoring logic for the dataclass-based API used by tests. main.py prints a readable ranked report, and README documents the data flow, recipe, and sample output. |
…sights; update main.py to include user profiles and adversarial cases; refine recommender.py scoring logic with dynamic weight constants for improved clarity.
…ation, intended use, and limitations to enhance understanding of the music recommender system.
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…anations
Add a working CLI-first simulation: load_songs parses data/songs.csv into typed dicts, score_song/_score_components apply the Algorithm Recipe (genre +2.0, mood +1.0, energy closeness up to +1.0, acousticness +0.5), and recommend_songs ranks the full catalog to return the top k with human-readable reasons. The OOP Recommender class shares the same scoring logic for the dataclass-based API used by tests. main.py prints a readable ranked report, and README documents the data flow, recipe, and sample output.