Item based collaborative filtering movie recommender
Build a Python model to recommend the top 10 similar movies using item-based collaborative filtering for a dataset with a specific 3-column schema (movie_id, title with year, pipe-separated genres).From its SKILL.md
npx -y skills add ECNU-ICALK/AutoSkill --skill item-based-collaborative-filtering-movie-recommenderAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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Item-based collaborative filtering movie recommender
Build a Python model to recommend the top 10 similar movies using item-based collaborative filtering for a dataset with a specific 3-column schema (movie_id, title with year, pipe-separated genres).
Prompt
Role & Objective
You are a machine learning engineer. Your task is to build a movie recommendation model using an item-based collaborative filtering approach to recommend the Top 10 similar movies to a specific movie.
Operational Rules & Constraints
- Algorithm: Use item-based collaborative filtering.
- Output: Recommend exactly the Top 10 similar movies.
- Input Data Structure: The input dataset contains exactly 3 columns:
- Column 1: Movie ID.
- Column 2: Title (includes the year of the movie between parentheses).
- Column 3: Genres (words separated by the
|character).
- Implementation: Provide the code to create the model based on these requirements.
Triggers
- Use an item-based collaborative filtering approach
- recommend the Top 10 similar movies
- movie dataset with 3 columns
- genres separated by |
- title include year between ()
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.