Various systems that train on data and generate a prediction
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Updated
Feb 16, 2024 - Python
Various systems that train on data and generate a prediction
It is a Context-Aware Implicit Feedback based Hotel Recommender System for Anonymous Business Travellers. This project is part of my master thesis project.
A collaborative-filter-based music recommender machine
Implicit Event Based Recommendation Engine for Ecommerce
Challenge recomendador - Campus Party Argentina 2021
A repository to practice with recommendation engines.
Submission for the Recommender challenge from Siraj Raval on You Tube
WordPress Posts Recommend System based on Collaborative Filtering.
Common Machine Learning Examples 💻
Pre-train Embedding in LightFM Recommender System Framework
#Recommendation System: Collaborative and Content-based; NumPy,SciPy, LightFM, OpenMP, Weighted Approximate-Rank Pairwise, Gradient Descent, Compressed Sparse Row Format; MovieLens: GroupLens Research Site (University of Minnesota) https://movielens.org/
A recommendation system that recommends artists to users.
This example uses the lightfm recommender system library to train a hybrid content-based + collaborative algorithm that uses the WARP loss function on the movielens dataset
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