GitHub topics: content-based-filtering
imtej/Recipe-Reccomendation-System
A personalized recipe recommendation system leveraging TF-IDF encoding and Content-Based filtering technique for dynamic recipe suggestions.
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MaklonFR/Movie-Recomendation-System
Submision Dicoding Indonesia - Machine Learning Terapan (Movie Recomendation)
Language: Jupyter Notebook - Size: 681 KB - Last synced at: 3 days ago - Pushed at: 4 months ago - Stars: 3 - Forks: 0

AadrianLeo/Book-Recommendation-System
Book Recommender System using the Book-Crossing dataset. Compares content-based (TF-IDF + cosine similarity) and collaborative filtering (SVD) methods for book recommendations. Includes data cleaning, EDA, and model evaluation (Precision@5, RMSE) in Python.
Language: Jupyter Notebook - Size: 59.7 MB - Last synced at: about 8 hours ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0

vb8146649/Movie-Recommender-System
The Movie Recommend System is a content-based movie recommendation engine that suggests similar films based on user input. Simply enter the name of a movie you like, and the system will return a curated list of titles that match its themes, genres, or style.
Language: Python - Size: 3.87 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 0 - Forks: 0

Sravyatogarla/Movie-recommendation-system
A complete Movie Recommendation System project implementing Popularity-Based, Content-Based, and Collaborative Filtering models using the MovieLens dataset. Built with Python, Pandas, and Plotly, featuring interactive inputs and visualizations.
Language: Jupyter Notebook - Size: 1.1 MB - Last synced at: about 8 hours ago - Pushed at: 13 days ago - Stars: 0 - Forks: 0

vb8146649/Book-Recommend-System
The Book Recommendation System is a content-based filtering project built using Python. It suggests books similar to a user’s input by analyzing textual features like the title, author, genre, and description. This system aims to help readers discover books that match their interests and reading preferences.
Language: Python - Size: 2.93 MB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 0 - Forks: 0

albertruaz/Recommendation-System
Language: Python - Size: 11.5 MB - Last synced at: 22 days ago - Pushed at: 22 days ago - Stars: 0 - Forks: 0

mozayed007/Media-Recommender
A recommendation system for Media Cross Types and Genres
Language: Jupyter Notebook - Size: 148 MB - Last synced at: 25 days ago - Pushed at: 25 days ago - Stars: 0 - Forks: 0

al4744/rec-system
🎵 A Python-based content recommendation system using ML algorithms and matrix factorization techniques to analyze 600k-song dataset. Combines SVD, NMF, Factorization Machines, and Direct Similarity for personalized music suggestions. Handles cold start, optimizes with weighted similarity, and includes tools for visualization & evaluation.
Language: Jupyter Notebook - Size: 1.93 MB - Last synced at: 29 days ago - Pushed at: 29 days ago - Stars: 0 - Forks: 0

CSFelix/recommendation-system
✨ Recommendation Systems Using Diverse Techniques ✨
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CSFelix/recommendation-system-mba-usp-esalq
✨ Recommendation Systems Using Diverse Techniques ✨
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vishal220703/Book-Recommender-System
A Flask-based book recommendation system that suggests similar books using collaborative filtering and precomputed similarity scores.
Language: Jupyter Notebook - Size: 65.2 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

Shaik-Suhail/Book-Recommendation-System
A simple Book Recommendation System that suggests books to users based on similarity scores using content-based filtering. Built with Python, it helps users discover books they might enjoy by analyzing features like title, author, and genre.
Size: 12.8 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

cerqueiraa23/Spotify-Powered-Music-Recommendation-System
A hybrid music recommendation system using Spotify API and Python. Combines audio feature analysis with popularity weighting to suggest personalized tracks.
Size: 3.91 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

HanugaFathurC/book-recommendation-system-ml
An intelligent book recommendation system using machine learning. The system is built with Content-Based Filtering (TF-IDF + Cosine Similarity) and Collaborative Filtering (RecommenderNet with deep learning) to suggest personalized book recommendations.
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zavarujs/EAFC-2025-Hybrid-Recommendation-System-
Language: Jupyter Notebook - Size: 2.02 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

abburi33/Spotify-Powered-Music-Recommendation-System
A hybrid music recommendation system using Spotify API and Python. Combines audio feature analysis with popularity weighting to suggest personalized tracks.
Size: 1.95 KB - Last synced at: 25 days ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

HrishikeshSuchindra/Tamil-Movie-Recommendation-System-using-NLP
A content-based movie recommendation system using Natural Language Processing (NLP) techniques on Tamil movie reviews. The system utilizes TF-IDF vectorization and cosine similarity to suggest movies based on user preferences or input reviews.
Language: Jupyter Notebook - Size: 7.65 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

RedDotz20/news-content-recommender-system
📰 ArticleHorizon is a smart news article recommender webapp that helps users discover relevant and engaging content tailored to their interests.
Language: TypeScript - Size: 1.56 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

Mohabdo21/HybridRec-ContextEnrichment
An advanced hybrid recommendation system that combines collaborative filtering and content-based filtering approaches, enhanced with temporal awareness and contextual personalization
Language: Python - Size: 2.49 MB - Last synced at: 16 days ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

BigBeanTheory/Movie-Recommendation-System
A Streamlit-based web app that suggests movies using a content-based filtering model, built with Python, Pandas, and Scikit-learn. Leverages TMDB data to recommend films based on genres, keywords, cast, and crew, with posters fetched via API.
Language: Jupyter Notebook - Size: 9.59 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

docsallover/music-recommendation
Machine Learning Music Recommendation System: Hybrid Approach (Content & SVD) with Flask
Language: Python - Size: 4.08 MB - Last synced at: about 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

evelyncy96/Movie-Recommendation-System
We create movie recommendation system through demographic filtering, content-based filtering, collaborative filtering, and hybrid engine.
Language: Python - Size: 104 KB - Last synced at: 13 days ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

philiptitus/Collaborative-Book-Recommender
Made use of the content-based filtering algorithm to make a book recommender model
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mrnust/Recommendations-System
Content Based Filtering
Language: Jupyter Notebook - Size: 21.5 KB - Last synced at: 4 days ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

joffinjoy/o-horizon-recommendation
Reference repository for the O-Horizon Recommendation Engine featured in Neo4j Graphversation Episode 2
Language: JavaScript - Size: 15 MB - Last synced at: 2 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 2

Sourabh-Kumar04/Raso-movie-recommendation
Raso Movie Recommendation System is an AI-powered web application that suggests movies based on user preferences, genres, ratings, and similarity scores. It leverages machine learning techniques to enhance recommendations.
Language: Jupyter Notebook - Size: 8.67 MB - Last synced at: about 1 month ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

prince7711sharma/Movie-Recommender
Movie Recommendation System This repository contains a Python-based Movie Recommendation System that leverages Machine Learning and Vectorization methods such as TF-IDF to recommend movies based on content similarity. The system processes datasets containing movie information like titles, genres, and descriptions to generate accurate and efficient
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SciddhantoSinha/Book-Recommender-System-Using-Collaborative-Filtering
This project implements a book recommendation system using machine learning techniques. It helps users find books based on preferences, book ratings, and similarity measures.
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Juwono136/book-recommendation-system-using-content-based-filtering-and-collaborative-filtering
Book recommendation system using model development with Content-Based Filtering and Collaborative Filtering techniques.
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gargibendale/MyntraFit
Language: Jupyter Notebook - Size: 8.22 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

raquelanamb/harmonaic
A music recommendation assistant.
Language: Python - Size: 26.8 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 1

anwesha0123/Unsupervised_Learning_Practice
This repository contains a collection of unsupervised learning projects leveraging machine learning techniques such as clustering, dimensionality reduction, and anomaly detection. These projects are designed to extract meaningful insights from unlabeled data using algorithms like K-Means, DBSCAN, PCA, Autoencoders, and more.
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guidasneves/spotify_recsys
End-to-end Spotify recommendation system
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karenwky/Recommendation_System_Allrecipes
recommending recipes with content-based filtering approach
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hk-kumawat/Movie-Recommender-System
🎬 It helps you discover films. Search for your favorite movies, get a "Surprise Me" pick, and explore trending movies—all while viewing live details like posters, trailers, ratings, and cast information.
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yash1th-yerra/Hybrid-Model-Movie-Recommendation-System
This is an extension project to Movie-Recommendation-System https://github.com/yash1th-yerra/Movie-Recommendation-System.
Language: Jupyter Notebook - Size: 1.01 MB - Last synced at: 21 days ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

vsancnaj/Hybrid-Recommendation-System
A hybrid recommendation system combining Item-Based Collaborative Filtering and Content-Based Filtering to suggest skincare products based on user preferences, product ingredients, and ratings. Features a Flask API and an interactive Streamlit Web App for personalized recommendations.
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razamehar/Movie_Recommendation_System
This project employs multiple recommendation techniques, including popularity-based ranking with Bayesian averages, content-based suggestions using cosine similarity, and collaborative filtering via the Surprise library.
Language: Python - Size: 14.2 MB - Last synced at: 3 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

Rohansoni45/movie-recommendation-system
This project is a Content-Based Recommender System that suggests movies to users based on their preferences and watched history. The system leverages cosine similarity to find and recommend movies similar to a selected title. It is built using Python and libraries like Pandas, NumPy, and Scikit-learn.
Language: Python - Size: 2.06 MB - Last synced at: 2 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

soumyajit4419/Movie_Recommender_System
Recommending movies to user using various Colaborative Filtering and Content Based Filtering.
Language: Jupyter Notebook - Size: 3.12 MB - Last synced at: 30 days ago - Pushed at: about 5 years ago - Stars: 7 - Forks: 1

bimarakajati/Anime-Recommender-System
This project analyzes anime recommendation data using two approaches: Content-Based Filtering with K-Nearest Neighbors (KNN) and Collaborative Filtering with the RecommenderNet model. Data is taken from the Anime Recommendations Database, and various techniques such as TF-IDF and Early Stopping are used to improve model accuracy.
Language: Jupyter Notebook - Size: 4.23 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

abhipatel35/MovieMatcher-Movie-Recommender-System
A robust movie recommendation system using the MovieLens dataset, employing Collaborative Filtering, Matrix Factorization, and Hybrid Models to enhance recommendation accuracy and diversity.
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DragoKami/Anime-Recommendation-System-Amime2022-dataset
Anime Recommendation System for websites with EDA
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Aksoni07/Movie-Recommendation
A hybrid movie recommendation system designed to deliver personalized and accurate suggestions by combining user preferences, item attributes, and collaborative patterns, ensuring a seamless and engaging experience.
Language: Jupyter Notebook - Size: 1.16 MB - Last synced at: 23 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 1

Upasanadhameliya/Django-Movie-Recommendor
Movie Website built on python Django framework; Uses Content Based Predictive Model approach to predict similar movies based on the contents/genres similarities
Language: Python - Size: 62.8 MB - Last synced at: about 2 months ago - Pushed at: almost 5 years ago - Stars: 14 - Forks: 5

ChoukriLach/Movie-Recommendation-Systems
Build movie recommender systems with a collaborative filtering approach and a content-based deep learning method
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AxelSeanCP/Anime-Recommender-System
A Project from Dicoding's Machine Learning Expert Class. Recommender System for Anime using Content-Based Filtering and Collaborative Filtering
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gerinsp/Movie-Recommendation-System
Developed a Movie Recommendation System using content-based filtering and collaborative filtering to suggest personalized movie recommendations.
Language: Jupyter Notebook - Size: 299 KB - Last synced at: 3 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

jnopareboateng/Lhydra_rs
Journey detailing Lhydra Hybrid Music Recommender System
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easonlai/content_based_product_recommendation_samples
The sample code repository leverages Azure Text Analytics to extract key phrases from the product description as additional product features. And perform text relationship analysis with TF-IDF vectorization and Cosine Similarity for product recommendation.
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maulanakavaldo/movie-recommendation-system
Language: HTML - Size: 201 KB - Last synced at: 3 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

Yukta026/book_recommender_system
I have created a book recommender system that recommends similar books to the reader based on his/her interest. This project shows results of collaborative and content-based filtering of the given dataset.
Language: Jupyter Notebook - Size: 39.9 MB - Last synced at: 3 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

Nourine-Nadir/Movie-Recommander-system-Content-based-
A Movie Recommender System implemented in Python using content-based filtering techniques. The system processes a dataset of 10,000 movies, extracting features such as keywords, genres, cast, and crew information to generate movie recommendations based on user input.
Language: Jupyter Notebook - Size: 2.98 MB - Last synced at: 3 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

codeasarjun/MovieMingle
Movie Recommendation System is a web application designed to provide personalized movie recommendations to users based on their input movie titles.
Language: Python - Size: 75.1 MB - Last synced at: 3 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

yajasarora/Movie-Recommendation-Model-using-NLP-Techniques
A content-based movie recommendation model using NLP techniques to analyze and suggest movies based on metadata like genres, keywords, and plot summaries.
Language: Jupyter Notebook - Size: 8.74 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 0

Aaryan015/AI-book-recommender-system
Hybrid recommender system - Collaborative filtering + Content based filtering (same as used by Netflix).
Language: Jupyter Notebook - Size: 6.16 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

amalaluan/wa_mern_project-peso
A MERN stack-based automated job portal integrating a content-based algorithm to match candidates with relevant job opportunities. Features include user registration, job listing management, resume submission, and job application tracking.
Size: 2.93 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

AhmedShoeb0/MovieRecommenderSystem
A simple movie recommender system that uses two main approaches to make recommendations: Content-based algorithm and Collaborative filtering algorithm (User-based).
Language: Python - Size: 14.3 MB - Last synced at: 10 months ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

farhanazmiCS/triprecco-public
Don't know where to go next? Let Triprecco for you!
Language: Python - Size: 1.32 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

Maoelan/indo-tour-recommend
Dicoding Submission Machine Learning Terapan
Language: Jupyter Notebook - Size: 454 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 2 - Forks: 0

sharmeen-k/Movie-Recommender-System
A content-based system recommends movies to an input user based on the weighted genre score of a movie and a collaborative filtering system recommends movies liked by other users having a similar taste profile as the input user.
Language: Jupyter Notebook - Size: 39.1 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

jss415/recommendation-system
Evaluation of Recommendation Systems
Language: Jupyter Notebook - Size: 1.05 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

Nathius262/trend-fitness-recommendation-technique
Trend Fitness is a web application dedicated to providing professional fitness advice which will include a range from fitness plans to diet plans catered to every individual needs. I believe that my web application will embark on a transformative journey towards a healthier lifestyle.
Language: Jupyter Notebook - Size: 586 KB - Last synced at: 3 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 1

jmarihawkins/neural-network-challenge-1
The purpose of this project is to predict student loan repayment success using a neural network. Neural networks are computational models inspired by the human brain's structure and function, consisting of layers of interconnected nodes or "neurons" that can learn to recognize patterns in data.
Language: Jupyter Notebook - Size: 36.1 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

heddgehogg/gamerecomsystem
The purpose of this project is to develop a recommender system based on content-based filtering in the Python programming language.
Language: Jupyter Notebook - Size: 68.5 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

convenience-tinashe-chibatamoto/Movie-Recommendation-System
A movie recommendation system using IMDb's weighted ratings and custom filters.
Language: Jupyter Notebook - Size: 112 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

saivikas1/Music-Recommender-System
Language: Python - Size: 29.1 MB - Last synced at: 4 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Manu-Abuya/Music-Recommendation-System
Build a personalized Music Recommendation System using Spotify API and Python. The system uses content-based and hybrid filtering to suggest songs based on user preferences, enhancing the music discovery experience.
Language: Jupyter Notebook - Size: 17.6 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

adrianmarino/thesis-paper
Collaborative and hybrid recommendation systems
Language: Jupyter Notebook - Size: 353 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 1

jtonglet/Recommender-Systems-Polimi
Competition for the Recommender Systems course @ PoliMi. The objective is to recommend relevant TV shows to users. Models were evaluated on their MAP@10.
Language: Python - Size: 16.7 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 1

Ayushma00/Text-Mining-and-Recommendation-System-for-Yelp-Dataset-
Restaurant Recommendation Application
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shadowbourne/CACBCF-Recommender-System
3rd Year: 1st - 92. A Novel Context Aware Restaurant Recommender System Using Content-Boosted Collaborative Filtering (CACBCF).
Language: Python - Size: 43.1 MB - Last synced at: about 1 year ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 1

DDILLOUD/Spotify-AI-Music-Recommender
AI Music Rec w/ Spotify & Streamlit
Language: Python - Size: 0 Bytes - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

mariodmtrv/music-recommendations
Music recommender system with collaborative and content-based filtering
Language: Python - Size: 22.5 KB - Last synced at: about 1 year ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 1

TommyNiemi/RECOMMENDER_SYSTEM
A movie recommender. Collaborative and content based filtering hybrid model.
Language: HTML - Size: 1.61 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

vishant-mehta/Music-Recommendation-System-using-Cosine-Similarity
The recommender framework goes about as a friend in need and channels the melodies that are reasonable for that client at that point. It likewise expands the client's fulfilment by playing fitting tune at the correct time, and, in the interim, limit the client's work.
Language: Jupyter Notebook - Size: 12.6 MB - Last synced at: about 1 year ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

PhamThe-KHDL/DS300.N11-Recommendation-System
DS307.N11 - Hệ Khuyến Nghị
Language: Jupyter Notebook - Size: 39.7 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

ojasvi004/News-Recommendation-System
The News Article Recommendation System is a project designed to provide personalized article recommendations based on the content of news headlines.
Language: Jupyter Notebook - Size: 107 KB - Last synced at: about 1 year ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

namunaacharya/nextread
NextRead is a book recommender system built for Book Lovers. Simply enter your current favourite book and get peronalized book list to find your new favourite.
Language: HTML - Size: 34.6 MB - Last synced at: about 1 month ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

itsLeonB/workout-recommender-api
API for Workout Recommender system. Built with FastAPI.
Language: Python - Size: 4.05 MB - Last synced at: 3 months ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 1

pm390/recsys2022
Code repo of solution of 11th place in Recsys Challenge 2022
Language: Jupyter Notebook - Size: 1.36 MB - Last synced at: 11 months ago - Pushed at: almost 3 years ago - Stars: 10 - Forks: 3

sree7k7/AmazonEventBridge-filtering-rule-to-trigger-lambda
AmazonEventBridge with content based filtering rule to trigger lambda function
Language: Python - Size: 43 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

SBwho/Movie-Recommendation-System
Movie Recomendation System is a movie recommender system using the TMDB 5000 Movie Dataset on Kaggle. Main goal of this system is to develop essential skills in data handling, exploratory data analysis, and model building
Language: Jupyter Notebook - Size: 41 KB - Last synced at: 3 months ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

tohid-yousefi/Content_Based_Recommender_Systems
in this section will be content recommender systems on movies meta dataset
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ipekdogabedirhan/Content_Based_Recommenders
In this section, we will create a recommendation system on the movie meta dataset.
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siniekoo19/Content-Based-Movie-Recommandation-System
Movie Recommandation System Based on the item profile
Language: Jupyter Notebook - Size: 1.05 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

esha411/Mr.MealMuse
Satisfy your food cravings with a personalized recommendation.
Language: Jupyter Notebook - Size: 8.17 MB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

AhmedShoeb0/BooksRecommenderSystem
A simple books recommender system that provides the functionality to ask for books recommendations or search for them using various options.
Language: Python - Size: 9.38 MB - Last synced at: 10 months ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 0

nsimona/giveapaw
A full-stack pet adoption app, featuring a comprehensive platform for users and adoptable pets. Future-proofed with a content-based recommendation engine for potential ML advancements.
Language: TypeScript - Size: 14.8 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

devidutta-learn/movie-recommender-system
This code and data create a movie recommender system using content based filtering and cosine similarity. It uses the features of movies (genre, crew, etc.) to find and suggest similar movies to users.
Language: Jupyter Notebook - Size: 1.94 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

chen0040/mxnet-recommender
Collaborative Filtering NN and CNN based recommender implemented with MXNet
Language: Python - Size: 120 MB - Last synced at: 2 months ago - Pushed at: about 7 years ago - Stars: 12 - Forks: 1

SebastianRokholt/Hybrid-Recommender-System
A repository for a machine learning project about developing a hybrid movie recommender system.
Language: Jupyter Notebook - Size: 13.5 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 35 - Forks: 13

jakeolase/rappp.ai
Recommender Application for Programming Languages, Projects, and Publication Paper using Content-Based Recommendation System and KeyBERT
Language: HTML - Size: 3.48 MB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

rooom13/recommendation-system-thesis
Recommendation Systems thesis. This repository contains the development of the evaluation of three recommendations system methods: Collaborative Filtering, Content Based and Hybrid.
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vinit714/A-Recommendation-system-for-Facial-Skin-Care-using-Machine-Learning-Models
Transforming skincare recommendations: our hybrid system combines KNN, CNN, and EfficientNet B0 for personalized advice. Published in IEEE, with 80% validation accuracy and 87.10% training accuracy.
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chen-jin021/music-rs
A dual-feature data portable MRS designed to predict user's music preferences under two recommending algorithms and bridge the gap between various music streaming platforms, notably Spotify and TIDAL.
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MChatzakis/DIS-RecommenderSystem
Movie Recommendations over the MovieLens dataset using Matrix Factorization
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richardoey/vector-space-model-skripsi 📦
Back End Coding for Final Project for "Implementation of Content-Based Filtering on Books Recommendation Application Using Vector Space Model <Case Studi: UMN Library>"
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PranjalAsthana/PickFlicks
AI based movie recommendation system using Content Based Filtering through Cosine Similarity Matrix.
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