Movie Recommendation System created using Collaborative Filtering (Website) and Content based Filtering (Jupyter Notebook)
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Updated
May 29, 2024 - Jupyter Notebook
Movie Recommendation System created using Collaborative Filtering (Website) and Content based Filtering (Jupyter Notebook)
This repository contains introductory notebooks for recommendation system.
A python notebook for building collaborative, content-based, and ml-based recommender systems with Sklearn and Surprise
A notebook for movie and TV show recommendations using Boolean and TF-IDF methods. Get personalized suggestions based on text descriptions and choose the method that suits your preferences.
The complete recommender system using both Collaborative FIltering and Content based filtering approaches, in addition to a web crawler, an API and the main website.
This repository contains mini projects inData science in python with notebook files
This project developed two wine recommendation models using the XWines dataset, employing collaborative filtering and content-based techniques. It leveraged Python, Numpy, Pandas, Jupyter Notebook, VSCode, and Scikit-learn.
Sistema de Recomendacion de la plataforma Steam desarrollado
This repository hosts a Jupyter Notebook-based Comment Generation Tool exploring advanced NLP techniques for automated, contextually relevant comment generation from input data. Ideal for developers and researchers in NLP and automated text generation.
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