An Open Source Machine Learning Framework for Everyone
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Updated
Sep 9, 2021 - C++
An Open Source Machine Learning Framework for Everyone
Movie recommender system and noisy-or model practice.
Fast multi-threaded memory optimized tool to compute cosine similarity on very large matrices imported from NumPy.
Movie Recommendation System using Unification of User Based and Item Based Collaborative Filtering Methods by Similarity Fusion. Project was implemented in Python using flask.
Code and data-sets of the paper "Avoiding congestion in recommender systems."
A recommender system based on Non-negative matrix factorization
Pyreclab is a library for quickly testing and prototyping of traditional recommender system methods, such as User KNN, Item KNN and FunkSVD Collaborative Filtering. It is developed and maintained by Gabriel Sepúlveda and Vicente Domínguez, advised by Prof. Denis Parra, all of them in Computer Science Department at PUC Chile, GRIMA Lab and SocVis…
Cryptocurrency Recommendation based on Tweets
📚 Goodreads, Operating Systems course, University of Tehran
Factorization Machine with pairwise loss for LTR problems
Data Science, Spring 2020, Hanyang University.
Road network partitioning strategy for faster queries in recommender systems
Trabalho Prático desenvolvido durante o curso de Programação e Desenvolvimento de Software II
(Class) C++ script to preprocess input files (mapping ids to indices and vice versa) on a single core machine.
A C++ implementation of MPR(Multi-Objective Pairwise Ranking)
Collaborative Denoising Auto-Encoder for Top-N Recommender Systems
Distributed recommender system based on Co-Clustering
A movie recommendation system, or a movie recommender system, is an ML-based approach to filtering or predicting the users' film preferences based on their past choices and behavior.
GPGPU Parallel User-User Collaborative Filtering System in CUDA C
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