Personalized book recommender system to generate top 5 recommendations to users
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Nov 12, 2017 - Jupyter Notebook
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scikit-surprise
Here are 32 public repositories matching this topic...
This project aims to build & optimise a book recommendation system based on collaborative filtering and will tackle an example of both memory based & model based approach (using KNNWithMeans & Singular Value Decomposition)
numpy plotly pandas accuracy recommender-system singular-value-decomposition scikit-surprise knnwithmeans
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Mar 26, 2022 - Jupyter Notebook
This repo contains my practice and template code for all kinds of recommender systems using SupriseLib. More complex and hybrid Recommender Systems can build on top of these template codes.
python evaluation python3 collaborative-filtering recommender-system jupyter-notebooks content-based-recommendation surprise-python hybrid-recommender-system scikit-surprise surprise-library
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Jul 24, 2020 - Python
Food Finder: An interface for a multi-user recommendation system.
natural-language-processing collaborative-filtering matrix-factorization restaurants recommendation-system latent-dirichlet-allocation user-reviews yelp-dataset content-based-recommendation hybrid-recommender-system las-vegas scikit-surprise knowledge-based-recommendation gensim-topic-modeling folium-maps
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Mar 11, 2021 - Jupyter Notebook
Machine Learning Music Recommendation System: Hybrid Approach (Content & SVD) with Flask
flask machine-learning numpy scikit-learn ml pandas music-recommendation seaborn scipy matplotlib svd surprise scikit-surprise content-based-filtering
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Apr 8, 2025 - Python
Recommender system that applies a user-to-user collaborative filtering algorithm on the MAL dataset to recommend anime for users.
python machine-learning anime python3 collaborative-filtering recommender-system myanimelist surprise-python scikit-surprise mal-dataset
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Apr 23, 2018 - Python
Adaptive Learning Recommendation System using collaborative filtering to suggest personalized learning materials based on student engagement and performance metrics.
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Nov 2, 2025 - Jupyter Notebook
A machine learning recommendation engine using Collaborative Filtering and Matrix Factorization on the MovieLens dataset.
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Jan 17, 2026 - Jupyter Notebook
Common Machine Learning Examples 💻
python nlp opencv machine-learning deep-learning random-forest tensorflow svm naive-bayes genetic-algorithm scikit-learn keras pandas object-detection decision-trees tpot textblob lightfm svr scikit-surprise
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May 11, 2019 - Python
A Wine Recommender System (My Capstone project for Data Science Immersive course)
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Nov 30, 2022 - Jupyter Notebook
🎵 SVD-based collaborative filtering recommender system — 100K MovieLens ratings, 3-fold cross-validation, RMSE/MAE evaluation, Top-N personalized recommendations, and structured logging. Built with Python & scikit-surprise.
python nlp data-science machine-learning numpy cross-validation collaborative-filtering matrix-factorization recommendation-engine recommender-system svd movielens scikit-surprise ratings-prediction
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May 1, 2026 - Python
A repository containing various projects and microprojects.
python data-science machine-learning deep-learning clustering numpy scikit-learn regression pandas data-visualization classification dimensionality-reduction data-analysis survival-analysis matplotlib keras-tensorflow time-series-analysis lifelines scikit-surprise
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Jun 15, 2023 - Jupyter Notebook
A collaborative filtering recommendation system built with Python, Pandas, and Scikit-Surprise.
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Sep 22, 2025 - Jupyter Notebook
This project is a movie recommender engine written using Python and the Scikit-Surprise libraries to generate better movie recommendations by utilizing temporal user interactiondata.
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Nov 4, 2023 - Python
Manga Recommender Systems based on Anilist API
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Aug 18, 2025 - Jupyter Notebook
Movie Recommendation using SVD Algorithm
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Apr 14, 2023 - Jupyter Notebook
RECOMMENDER for films >= 2010. Uses Scikit-Surprise.
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Mar 4, 2021 - Jupyter Notebook
This project aims to build an advanced book recommendation system by integrating collaborative filtering, content-based filtering, and machine learning. It offers tailored suggestions based on user preferences and interactions, using EDA for insights and cosine similarity and SVD for precise recommendations.
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May 11, 2024 - Jupyter Notebook
Movie recommendation engine comparing SVD, User-CF & Item-CF on 100K MovieLens ratings
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Mar 2, 2026 - Jupyter Notebook
Simple Recommender System built using the Scikit Surprise Library. The application provides recommendations based on Amazon Products Reviews.
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Jul 4, 2021 - Jupyter Notebook
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