Designed a movie recommendation system using content-based, collaborative filtering based, SVD and popularity based approach.
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Updated
Sep 14, 2020 - Jupyter Notebook
Designed a movie recommendation system using content-based, collaborative filtering based, SVD and popularity based approach.
Grocery Recommendation on Instacart Data
This repository contains collaborative filtering recommender system build in Python with surprise package to predict book ratings in Book-Crossing dataset.
Built a collaborative filtering and content-based recommendation/recommender system specific to H&M using the Surprise library and cosine similarity to generate similarity and distance-based recommendations.
Comparing different recommendation systems algorithms like SVD, SVDpp (Matrix Factorization), KNN Baseline, KNN Basic, KNN Means, KNN ZScore), Baseline, Co Clustering
Exploring Recommender Systems using various Machine Learning Models like scikit-learn, Surprise, NLP and collaborative filtering using KNN and Tensorflow.
Phase 4 project of the Flat Iron curriculum of Data Science in Moringa School
Recommendation Systems tutorial
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.
Implementation of the model iGSLR
Hybrid RecSys, CF-based RecSys, Model-based RecSys, Content-based RecSys, Finding similar items using Jaccard similarity
Use the Scikit-Network for PageRank algorithms including Topic-specific PR and improve the performance of various recommendation-systems using Surprise library
Machine Learning homework project at EPFL
This program combines several recommendation approaches in order to predict and display to users recommendations of hotels located in the Paris area.
Suprise-Python Wrapper for Persa.jl
This is a recommendation system based on Singe value Decomposition method ( Collaborative filters )
울산 맛집,카페/명소 추천 시스템
Getting a better grasp of recommender systems
Recommend Airbnb Listings to the User based on reviews.
Recommender System built using Python, Angular, Firebase & MySQL
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