klhhrx/Reel-Rec

Reel Rec - A Movie Recommendation AI designed to change the way movie enthusiasts discover and enjoy favorite films. Made using Django & Tailwind CSS.

Size: 1.95 KB - Last synced at: about 9 hours ago - Pushed at: about 10 hours ago - Stars: 0 - Forks: 0

Dicoding-Addin/ML-Terapan-Akhir

Proyek Akhir ML-Terapan

Language: Jupyter Notebook - Size: 2.14 MB - Last synced at: about 14 hours ago - Pushed at: about 15 hours ago - Stars: 0 - Forks: 0

asdhasdasj/Reel-Rec

Reel Rec - A Movie Recommendation AI designed to change the way movie enthusiasts discover and enjoy favorite films. Made using Django & Tailwind CSS.

Size: 1.95 KB - Last synced at: about 19 hours ago - Pushed at: about 20 hours ago - Stars: 1 - Forks: 0

andremedina15/Reel-Rec

Reel Rec - A Movie Recommendation AI designed to change the way movie enthusiasts discover and enjoy favorite films. Made using Django & Tailwind CSS.

Size: 1.95 KB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 8 - Forks: 0

Demetreous/Spotify-Track-Recommender-System-and-Popularity-Regression

ML project leveraging Spotify audio data for track popularity prediction and music recommendation using XGBoost, KNN, and SHAP

Language: Jupyter Notebook - Size: 1.99 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0

RAHEEM12344/content-recommendation-engine

A modern, responsive web application that delivers personalized content recommendations based on user preferences and behavior. This interactive recommendation system allows users to discover content tailored to their interests through category selection, tag filtering, and customizable content parameters.

Language: HTML - Size: 187 KB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0

Aries921wu/Highly-Robust-Movie-Recommendation-engine

A highly sophisticated, tested, robust and procedural recommender.

Language: Python - Size: 35.7 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 0 - Forks: 0

DevJinah/collaborative-book-recommender

Collaborative filtering based book recommendation system

Language: Jupyter Notebook - Size: 15.3 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 0 - Forks: 0

Soriano-R/Recommendations_with_IBM

A recommendation system for IBM Watson Studio platform that analyzes user-article interactions and suggests relevant content using multiple recommendation techniques

Language: HTML - Size: 4.38 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 0 - Forks: 0

aragaoian/adopet-rs

Recommender System based on feature weighted Content-Based Filtering.

Language: Python - Size: 34.2 KB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 0 - Forks: 0

fatihilhan42/Movie_Recommendation_System

This project includes a system that provides personalised movie recommendations to movie lovers. Using TF-IDF and cosine similarity algorithms, it finds similar films based on a user-selected film title.

Language: Jupyter Notebook - Size: 10.9 MB - Last synced at: 1 day ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

keerthivnair/Movies_Recommendation_System

This is a movie recommendation system.

Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 0 - Forks: 0

andreeaiana/newsreclib

PyTorch-Lightning Library for Neural News Recommendation

Language: Python - Size: 572 KB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 53 - Forks: 12

imtej/Recipe-Reccomendation-System

A personalized recipe recommendation system leveraging TF-IDF encoding and Content-Based filtering technique for dynamic recipe suggestions.

Language: Jupyter Notebook - Size: 878 KB - Last synced at: 3 days ago - Pushed at: 20 days ago - Stars: 0 - Forks: 0

zenklinov/IBM_Machine_Learning_Capstone

This repository contains materials for the Machine Learning Capstone course offered by IBM. Build a course recommender system, Analyze course-related datasets, and Generate recommendation systems using techniques such as KNN, PCA, and non-negative matrix collaborative filtering

Language: Jupyter Notebook - Size: 3.29 MB - Last synced at: 23 days ago - Pushed at: 4 months ago - Stars: 2 - Forks: 1

ridopandiSinaga/System-Recommendation

Applied Machine Learning - book system Recommender using Content based and Collaborative Filtering (Deep Learning Model Based)

Language: Jupyter Notebook - Size: 351 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 2

stanleyfok/content-based-recommender

A simple content-based recommender implemented in javascript

Language: JavaScript - Size: 521 KB - Last synced at: about 15 hours ago - Pushed at: over 2 years ago - Stars: 63 - Forks: 19

aniass/books-recommender-system

The books recommendation system using collaborative filtering and content-based filtering methods.

Language: Jupyter Notebook - Size: 466 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 2 - Forks: 0

swapUniba/ClayRS

Complexly represent contents, build recommender systems, evaluate them. All in one place!

Language: Python - Size: 32.5 MB - Last synced at: 15 days ago - Pushed at: over 1 year ago - Stars: 36 - Forks: 5

netesy/Caidin

A recommendation engine for the clever. Caidin is a Python library that empowers developers to build smart recommendation systems, including content-based and collaborative filtering methods, making personalized recommendations a breeze.

Language: Python - Size: 19.5 KB - Last synced at: about 1 month ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

Bhasha03/Highly-Robust-Movie-Recommendation-engine

A highly sophisticated, tested, robust and procedural recommender.

Language: Python - Size: 35.7 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

Shanmukhi1920/H-M-Recommendation-System

Develop personalized product recommendations for H&M's users using transaction history, customer data, and product metadata (including text descriptions) to enhance shopping experience and sustainability.

Language: Jupyter Notebook - Size: 4.4 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

jash0803/financial-asset-recommendation

A hybrid financial asset recommendation system combining collaborative filtering, content-based methods, and questionnaire-driven risk profiling, for personalized investment suggestions.

Language: Python - Size: 11.1 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 1

HongTin2104/VietNam-Travel-Recommendation-System

A Streamlit web application that recommends tourist destinations in Vietnam based on three user-provided keywords. The dataset contains information about landmarks and attractions across 63 provinces. Users enter keywords to receive tailored suggestions, helping them explore the most suitable destinations.

Language: Python - Size: 287 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

HKUDS/LLMRec

[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"

Language: Python - Size: 8.34 MB - Last synced at: about 2 months ago - Pushed at: about 1 year ago - Stars: 454 - Forks: 56

threnjen/boardgamegeek

BoardGameGeek Recommender System is a start-to-finish project, from sourcing the data to a hybrid recommender system utilizing both content-based and collaborative filtering.

Language: Jupyter Notebook - Size: 186 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

KARTHICK-231801079/A123331-Foml-Mini-Project

Movie Recommendation System

Language: HTML - Size: 4.03 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

sisinflab/elliot

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

Language: Python - Size: 78.4 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 288 - Forks: 51

khanhnamle1994/movielens

4 different recommendation engines for the MovieLens dataset.

Language: Jupyter Notebook - Size: 41.9 MB - Last synced at: about 1 month ago - Pushed at: almost 6 years ago - Stars: 436 - Forks: 186

Poopman555/Spotify-Music-Recommendation-System

Music recommendation system that leverages the power of machine learning to provide personalized music suggestions based on user preferences. Using a hybrid approach combining K-Means Clustering and Cosine Similarity.

Size: 1000 Bytes - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 6 - 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: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

hadush-negasi/recipe-recommender

A content and collaborative filtering-based recipe recommendation system built with Streamlit and Firebase

Language: Jupyter Notebook - Size: 74.9 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

costadev00/youtube-public-feedback-and-content-suggestions

Sentiment Analysis from social media with powered marketing content cretion generation

Language: Python - Size: 2.74 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

jalajthanaki/Movie_recommendation_engine

This repository contains the code for building movie recommendation engine.

Language: Jupyter Notebook - Size: 7.02 MB - Last synced at: 19 days ago - Pushed at: about 7 years ago - Stars: 77 - Forks: 53

philiptitus/Collaborative-Book-Recommender

Made use of the content-based filtering algorithm to make a book recommender model

Language: Jupyter Notebook - Size: 10.7 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

affec-ds/Netflix-Recommender-System

Sistema de recomendación de títulos de Netflix basado en contenido. Incluye filtros por título, género y tipo de contenido (películas o series) con interfaz interactiva en Jupyter Notebook.

Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

sidyr6002/Zee-Recommender-System

A movie recommendation system

Language: Jupyter Notebook - Size: 8.01 MB - Last synced at: 3 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

bryanmanobanda/restaurant-recommendation-system

A restaurant recommendation system designed to enhance tourists' dining experiences by seamlessly integrating their personal preferences and real-time location through a hybrid algorithm for more accurate and personalized suggestions

Language: TypeScript - Size: 453 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

AdityaSreevatsaK/Suggestify-RecommendationSystems

Suggestify-RecommendationSystems is a dedicated repository for implementing and experimenting with traditional recommendation system techniques. It covers collaborative filtering, content-based methods, and hybrid approaches, focusing on practical and scalable solutions for personalised recommendations across various domains.

Language: Jupyter Notebook - Size: 13.5 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

jalajthanaki/Job_recommendation_engine

This repository contains code how to build job recommendation engine using Kaggle 'Job Recommendation Challenge' dataset

Language: Jupyter Notebook - Size: 147 KB - Last synced at: 3 months ago - Pushed at: about 7 years ago - Stars: 63 - Forks: 41

gargibendale/MyntraFit

Language: Jupyter Notebook - Size: 8.22 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

azita4/NextRead

NextRead is a book recommender system created specifically for book readers. It allows a user to get personalised recommendation with a user-friendly interface. This is my final year project.

Language: HTML - Size: 34.2 MB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

VyjayanthiPolapragada/GenAI_Smart_Retail_Recommendation

GenAI Smart Retail is a recommendation system designed for retail environments. It provides personalized product recommendations to users based on product descriptions using a content-based filtering approach. The system leverages FastAPI for backend integration, allowing users to interact with the recommendation engine via an API. This project aim

Language: Jupyter Notebook - Size: 316 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

pngo1997/Chicago-Airbnb-Hybrid-Recommender-System

Develops a hybrid recommender system for Chicago Airbnb listings using data from Inside Airbnb.

Language: Jupyter Notebook - Size: 30.9 MB - Last synced at: 16 days ago - Pushed at: 4 months ago - Stars: 2 - Forks: 0

Edolor/E-commerce-Recommendation-System

An e-commerce web application built using django and django-rest-framework, embedded with a content-based recommendation system.

Language: Python - Size: 43.4 MB - Last synced at: 5 days ago - Pushed at: over 1 year ago - Stars: 7 - Forks: 4

RohanKaran/MovieBuzz

It is a content based movie recommendations web app. Based on the user input, it recommends similar movies/webseries to the user using machine learning.

Language: JavaScript - Size: 7.73 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 11 - Forks: 3

MaurizioFD/RecSys2019_DeepLearning_Evaluation

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

Language: Python - Size: 216 MB - Last synced at: about 2 months ago - Pushed at: about 2 years ago - Stars: 987 - Forks: 249

egemenzeytinci/foxandbox

Content based movie recommendation system

Language: Python - Size: 3.43 MB - Last synced at: 2 months ago - Pushed at: 4 months ago - Stars: 4 - Forks: 0

MohitBharambe/Reel-Rec

Reel Rec - A Movie Recommendation App designed to change the way movie enthusiasts discover and enjoy favorite films. Made using Django & Tailwind CSS.

Language: HTML - Size: 21.3 MB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 5 - Forks: 0

pngo1997/Yelp-Business-Recommender-System

Building an item-based collaborative recommendation system using embeddings for establishments from the Yelp dataset.

Language: Jupyter Notebook - Size: 42.9 MB - Last synced at: 4 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

ns-nexus/Movie-Recommender-System

Movie Recommender System leverages a content-based approach, suggesting films to users based on the attributes of movies they have previously enjoyed. By analyzing movie metadata such as genre, cast, director, keywords, etc., this project offers personalized recommendations aligned with users' cinematic tastes.

Language: Jupyter Notebook - Size: 19.7 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

goamegah/Cornac-Recommender-System-Animes

Recommendation system

Language: Jupyter Notebook - Size: 4.09 MB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

SubhangiSati/E-Learning-Course-Recommendation-System

This Python-based project recommends e-learning courses based on user preferences and course similarities. It utilizes natural language processing (NLP) techniques for accurate course suggestions. It is an end-to-end project with its seamless frontend build on React

Language: Jupyter Notebook - Size: 439 KB - Last synced at: 3 months ago - Pushed at: 12 months ago - Stars: 5 - Forks: 1

pngo1997/Hyperlink-Analysis-Content-Based-Recommendation-System

Hyperlink Analysis using PageRank and HITS algorithms and simple Content-Based Recommendation System.

Language: Jupyter Notebook - Size: 230 KB - Last synced at: 4 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

maettuu/24HS-Essentials-in-Text-and-Speech-Processing

Repository for the course Essentials in Text and Speech Processing Fall 2024

Language: Python - Size: 16.6 KB - Last synced at: 6 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

badal39/Art-Reccomendation-System

the Baroque-inspired Art Recommendation System suggests personalized art by combining text and image features with BERT and ResNet-50.

Language: Jupyter Notebook - Size: 1.45 GB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 2

ashwinhprasad/Anime-Recommender-System

Anime Recommender System with various recommender system algorithms implemented in python

Language: Jupyter Notebook - Size: 475 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

mw-it/seo4all

seo4all provides a comprehensive checklist, general infos, documents, tips and tricks for professional seo (search engine optimization).

Size: 39.1 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

bhaskrr/book-recommender-system

A book recommender system using content based filtering

Language: Python - Size: 64.2 MB - Last synced at: 13 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

04bhavyaa/movie-recommender-system

Basic Content Based Recommendation System using Cosine Similarity

Language: Jupyter Notebook - Size: 8.7 MB - Last synced at: 14 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

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: 3 months ago - Pushed at: almost 5 years ago - Stars: 14 - Forks: 5

yash1th-yerra/Movie-Recommendation-System

This project is a content-based movie recommendation system built with the TMDb 5000 Movies and Credits datasets. It processes and combines movie metadata, including genres, keywords, cast, crew, production companies, and overview descriptions, to recommend movies based on similarity.

Language: Python - Size: 43 KB - Last synced at: 3 months ago - Pushed at: 6 months ago - Stars: 2 - Forks: 0

sammedkamate/movie-recommender-system

Language: Jupyter Notebook - Size: 15.1 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

iamdebasishdas123/Hybrid_Recommendation_System

This project implements a Recommendation System using data ingestion, preprocessing, and recommendation generation workflows.

Language: Jupyter Notebook - Size: 31.3 KB - Last synced at: 4 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

yuvraj-solanki-2406/movie-recommandation

Movie Recommendation System with Flask based web application with social connection setup

Language: HTML - Size: 14.2 MB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

kanugurajesh/Movie-Recommendation-System

A saas based application to recommend movies

Language: Jupyter Notebook - Size: 125 KB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 9 - Forks: 0

SathvikNayak123/RecSys-with-pysaprk

Built Content and Collaborative filtering based Recommendation system. Utilized PySpark to handle datasets with 3 Million+ entires.

Language: Jupyter Notebook - Size: 10.7 KB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

deliprofesor/Cinematic-Data-Analytics-and-Recommendation-Platform

This project analyzes a movie dataset using machine learning algorithms to predict success, explore revenue-popularity relationships, and develop recommendation systems. It employs techniques like K-Means, DBSCAN, GMM, decision trees, PCA, and NLP for insights and personalized suggestions.

Language: Python - Size: 1.83 MB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

jerinpious/Movie-Recommendation-System

A content-based movie recommendation system built using Python. The system processes movie data, extracts relevant features, and provides recommendations based on user preferences

Language: Jupyter Notebook - Size: 10.1 MB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

sleetymattgeorge/AI-Course-Recommendation-Chatbot Fork of m-kiran-g/AI-Course-Recommendation-Chatbot

This is a AI Course Recommendation chatbot based on Coursera Data using content/rule based algorithms.

Language: HTML - Size: 1.24 MB - Last synced at: 6 days ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 2

GURSV/RecipeRover-Production Fork of Garvit-Nag/RecipeRover-Production

End Sem Project - RecipeRover

Language: TypeScript - Size: 30.9 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

peelajanu/Case-Study--ML--Personalized-Stock-Investment-Advisor

The Personalized Stock Investment Advisor leverages machine learning to recommend stocks based on user preferences and market data, helping users make informed buy, hold, or sell decisions for optimized portfolios.

Size: 25.2 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

rpytel1/multimedia-project

Implementation of content based recommendation system using transformed data from Social Media Challenge. Similarity based and Machine Learning approaches implemented. Employed image features like: HOG histogram, HSV histogram and even SIFT descriptors.

Language: Python - Size: 104 MB - Last synced at: 4 months ago - Pushed at: almost 6 years ago - Stars: 3 - Forks: 0

AdrijaDastidar/Recommendation-System

Movie recommendation system

Language: Jupyter Notebook - Size: 856 KB - Last synced at: 4 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

karan3691/social-media-recommender

provides personalized content recommendations for users based on their interactions, preferences, and browsing history.

Language: Python - Size: 7.81 KB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

Yunanouv/Skin-Care-Recommender-System

Skin Care Recommender System Based on Skin Problems Using Content-Based Filtering

Language: Jupyter Notebook - Size: 4.02 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 8 - Forks: 1

eshita-jain/Book-Recommendation-System

Book Recommendation System- A Web app made using flask framework to recommend your favorite book using content based filtering and cosine similarity metrices.

Language: HTML - Size: 16.9 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 8 - Forks: 2

NajdBinrabah/Music-Recommendation-System

This project explores diverse "Recommendation Techniques", each offering a distinct approach to predicting user preferences.

Language: Jupyter Notebook - Size: 438 KB - Last synced at: 4 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

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.

Language: HTML - Size: 118 KB - Last synced at: 4 months ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 1

Rohit7594/Movie_Recommendation_System

Content Based - Movie recommender system. End-to-End project, deployed on Heroku

Language: Jupyter Notebook - Size: 2.31 MB - Last synced at: about 2 months ago - Pushed at: about 3 years ago - Stars: 5 - Forks: 1

Nukaze/spotify-recommendations

Implements a content-based recommendation system for Spotify using TF-IDF (Term Frequency-Inverse Document Frequency) and Cosine Similarity. The system analyzes song features to recommend similar tracks based on user preferences.

Language: Jupyter Notebook - Size: 95.8 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

arshad-khalid/music-recommendation-system

A simple Python program that recommends similar music based on user input, utilizing data sourced from a CSV file.

Language: Python - Size: 12.1 MB - Last synced at: 4 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

khuangaf/tibame_recommender_system

TibaMe 「打造智能推薦系統：用AI搞懂客戶精準行銷」 實作課程程式碼

Language: Jupyter Notebook - Size: 777 KB - Last synced at: about 2 months ago - Pushed at: almost 5 years ago - Stars: 18 - Forks: 8

SageRalph/TSR-Public

Public repository for the Isle of Wight Supply Chain (IWSC) dataset and the Transitive Semantic Relationships (TSR) inference algorithm for cold-start recommendations.

Language: Python - Size: 3.09 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 1

ry05/couReco

A basic Course Recommendation app project built with Streamlit

Language: Python - Size: 1 MB - Last synced at: 7 months ago - Pushed at: about 2 years ago - Stars: 16 - Forks: 9

PEDROPERDO/MLMLMLMLM

Caesar : Movie Recommendation System

Language: Jupyter Notebook - Size: 64.5 KB - Last synced at: 7 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

lixx21/book-recommender-system

using machine learning content based algorithm to build book recommendation system

Language: Jupyter Notebook - Size: 686 KB - Last synced at: 3 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

faisal-fida/Content-Based-Filtering-Model

This project implements a content-based filtering model for recommending movies. The model uses various features extracted from a dataset of the top 1000 movies from IMDb to compute similarities and recommend similar movies.

Language: Jupyter Notebook - Size: 195 KB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

richardwarepam16/movie-recommender-system-content-based

This is a movie recommender system performed with a data from kaggle about tmdb. It is purely content based.

Language: Jupyter Notebook - Size: 4.85 MB - Last synced at: 2 months ago - Pushed at: about 3 years ago - Stars: 6 - Forks: 0

Arjun-Regmi-Chhetri/SneakFit-AI-Based-Sneaker-Recommendation-System

SneakFit is an AI-powered platform that helps users find their perfect sneakers using content-based recommendation algorithms. It features personalized recommendations, dynamic product listings, secure user authentication, advanced search with filtering, and a responsive design.

Language: JavaScript - Size: 18.1 MB - Last synced at: about 1 month ago - Pushed at: 11 months ago - Stars: 2 - Forks: 0

JonFillip/lastfm_music_recommender

This projects aims to demonstrate an MLOps level-2 systems using Kubeflow and Vertex AI. The model is a content-based recommendation system that recommends similar tracks based the artist, song tags, and playcount of the current track.

Language: Jupyter Notebook - Size: 179 MB - Last synced at: 9 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

ulyazmah/book-recommendation

An end-to-end data science project involving exploratory data analysis, machine learning modeling and web app deployment of book recommendation system.

Language: Jupyter Notebook - Size: 32.2 MB - Last synced at: 10 months ago - Pushed at: over 2 years ago - Stars: 9 - Forks: 6

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: 4 months ago - Pushed at: 10 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: 11 months ago - Stars: 0 - Forks: 0

peterjprudhomme/Poetry-Pitch

A content based recommendation system for poetry including an interactive flask application.

Language: Jupyter Notebook - Size: 8.69 MB - Last synced at: 10 months ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

radismili/Mobile-games-recommender-system

Content-based mobile game recommender system using game similarities.

Language: Jupyter Notebook - Size: 527 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

ynpreet/Content-based-Movie-recommendation-system

Among the 3 types of recommendation engines, I have built a content-based recommendation engine using Python and Scikitlearn. I first understood basic concepts such as cosine distance, euclidean distance and when to use each of them. Finally, by using IMDB 5000 movie dataset built a content-based recommendation engine using CountVectorize and Cosine similarity scores between movies.

Language: Jupyter Notebook - Size: 9.77 KB - Last synced at: 10 months ago - Pushed at: over 4 years ago - Stars: 6 - Forks: 0

Ahmad-Ali-Rafique/Comment-Generation-Tool

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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gajendrasharma-github/Intelligent-Movie-Recommendation-App-utilising-TMDB-Api

End to End Machine Learning Project using Content Based Filtering

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karar-hayder/RecAnthology

RecAnthology (Recommended Anthology) is an intelligent recommendation system designed to curate collections of books, movies, and TV shows based on user preferences. By leveraging advanced algorithms and user feedback. RecAnthology aims to provide personalized recommendations that cater to individual tastes.

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