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jacob14047/Fidelio
Fidelio is a machine learning model from jacob14047. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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Downloads · 30 days
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Updated Feb 3, 2026
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From the Hugging Face model README
A pipeline movie recommendation system developed as part of the Machine Learning (ML) course.
This project implements one hybrid methodology to solve the cold-start problem and improve recommendation accuracy:
A feature-based machine learning approach that treats recommendation as a regression/ranking problem:
This project utilizes a custom dataset constructed by merging user ratings with rich movie metadata collected from multiple sources:
MovieLens Dataset
User–item ratings are derived from the MovieLens datasets provided by GroupLens Research.
These ratings form the backbone of the collaborative filtering pipeline.
The Movie Database (TMDB) API
Rich movie metadata (TMDB IDs, cast, crew, directors, genres) was collected programmatically via the TMDB API and used primarily for content-based modeling.
Rotten Tomatoes Reviews Dataset
A large-scale dataset of critic and audience reviews scraped from Rotten Tomatoes, used to enrich item representations and provide additional signals for cold-start movies and sentiment-aware modeling.
The complete documentation and the setup tutorial are not included in this repository.
You can see everything on Github: https://github.com/jacob14047/Fidelio