reccomendation-system

There are 23 repositories under reccomendation-system topic.

  • luisosorio3214/Machine-Learning-Projects-Python-

    A composition of Machine Learning Projects in python using algorithms in supervised, unsupervised, and deep learning.

    Language:Jupyter Notebook1200
  • moscardino1/frudrera

    FRUDRERA is an AI-powered recipe recommender that suggests recipes based on the ingredients detected in a photo of your fridge. It utilizes object detection and OCR to identify ingredients and recommend recipes accordingly.

    Language:Python1
  • shabiasaeed/SOEN471

    SOEN471 Project - Team 10 - Winter 2024

    Language:Jupyter Notebook1100
  • adenletchworth/Happier-Cinema

    Web Application for Movie Reccomendations using FAISS

    Language:Python00
  • Aibi-Green/Diet-Recommendation-System

    Diet Recommendation System using KNN and built with Python for backend, ReactJS for frontend, and Docker for fast deployment.

    Language:Jupyter Notebook0100
  • amolbudhiraja/feastfinder

    Project for HackSC (The University of Southern California Hackathon)

    Language:JavaScript0200
  • christakakis/SmokersCollabFilter

    Personalized smoking recommendations based on Collaborative Filtering.

    Language:Jupyter Notebook0100
  • CS-Edwards/vector_search_engine

    Building a Custom Vector Search Engine with Weaviate : The project discusses the architecture of Weaviate, an open-source vector database and provides a tutorial implementation of a custom vector search engine using Weaviate Cloud Service(WCS).

    Language:Jupyter Notebook0100
  • Dacker15/python-reccomendation

    An overview of reccomendation systems in Python

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  • Dacker15/r-reccomendation

    An overview of reccomendation systems in R

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  • JoexTitan/Spotify-Recommendation-App

    🎵 Unlock the Future of Music with Predictive Analysis!

    Language:Python0100
  • Kshitij-Shresth/Movie-Recommendation

    A Flask-based movie recommender system based on TF-IDF vectorization and cosine similarity.

    Language:Python00
  • Marc-Eid/GA360Recommender

    Collaborative Filtering based on Google Analytics 360 data from BigQuery.

    Language:HTML00
  • rezaafaisal/game-recommendation

    By using a dataset sourced from IMDb taken from the kaggle.com site. This system can provide video game recommendations based on their genre.

    Language:Jupyter Notebook0100
  • Rick0701/Videogames_Reccommendation

    Recommending videogames based on games and gamers similarity and segmenting gamers into groups of similar preferences

    Language:Jupyter Notebook0000
  • sharonmordechai/data-science-courses

    M.Sc. Courses in Data Science, including Machine Learning, Deep Learning, Statistics and Data Analysis, and Recommendation Systems.

    Language:Jupyter Notebook0100
  • sharonmordechai/recommendation-systems-final-project

    Exploring Bloom embeddings as a compression technique for recommendation algorithms. Aimed at reducing the size of large input and output dimensionalities to enhance training and deployment efficiency on devices with limited hardware. This project evaluates Bloom embeddings using various hash functions and compares them with alternative methods.

    Language:Python00
  • Aninditaacha/CODSOFT-TASK-3

    I developed a simple content-based recommendation system that suggests movies to users based on their preferences. Users can enter a movie they like, and the system recommends other movies with similar genres. This project helped me understand the basics of recommendation systems and content-based filtering techniques.

    Language:JavaScript10
  • atharva-narkhede/Market-Basket-Analysis-for-Amazon-Product-Recommedation

    Conducted Market Basket Analysis (MBA) on Amazon product dataset to enhance recommendations. Identified top-selling products and top products in each category using review count. Implemented asso- ciation rule mining for personalized recommendations. Evaluated effectiveness through metrics.

    Language:Jupyter Notebook101
  • CS-Edwards/book_recommender_system

    Reading Recommendation System: This project implements K Nearest Neighbor (kNN) Collaborative Filtering to build a book recommender system based on a publicly available dataset.

    Language:Jupyter Notebook10
  • d1b2/indian_dishes_reccomender_system

    Indian food reccomendor

    Language:Jupyter Notebook10
  • NikhilPanda01/CineSuggest_A_Personalized_Movie_Suggestion_System

    CineSuggest," an advanced movie recommender powered by machine learning, removes uncertainty in film selection, employing data-rich algorithms for personalization.

    Language:Jupyter Notebook10
  • Yehonatal/project-readmore

    Receive tailored suggestions for new reads based on your interests and books you have read before.

    Language:JavaScript