KDD17_FMG
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Updated
Mar 5, 2020 - MATLAB
KDD17_FMG
Probabilistic Matrix Factorization with Social Trust for Recommendation (Ma et al. SIGIR 2009)
A Recommender System for Metaheuristic Algorithms for Continuous Optimization Based on Deep Recurrent Neural Networks
A system to recommend movies according to ratings provided by users using Collaborative Filtering Learning Algorithm.
Andrew Ng's Machine Learning Course
MATLAB Implementation of the CGPRANK algorithm
Movie Recommendation using Cascading Bandits namely CascadeLinTS and CascadeLinUCB
A Probabilistic Graphical approach to detect different types of shilling attacks on Recommender Systems.
📊 📈 In depth explained my assignment solutions. Grade: 97.3%
Nonnegative matrix factorization with DAG constraints. A probabilistic formulation, variational learning.
The codes have been provided to support the article "Novel implicit-trust-network-based recommendation methodology", which has been published in Expert Systems With Applications. This algorithmic framework is abbreviated to ITNRM. It first generates implicit trust networks to find users' trustees or neighbors. And a novel recommendation methodol…
Machine Learning from Stanford University (Andrew Ng) - Assignments and Lectures
This repository shows code of programming tasks which I completed during Machine Learning course on Coursera.
This Repository contains Solutions to Lab Assignments/slides and my personal Notes of the Machine Learning (2022) from Stanford University on Coursera taught by Andrew Ng.
These are the solutions to the programming assigments from Andrew Ng's "Machine Learning" course from Coursera
MATLAB implemention of our TNNLS paper "Modeling Self-representation Label Correlations for Textual Aspects and Emojis Recommendation”
A reccommender system for jobs using Deep Auto Encoders and Fuzzy Clustering
This repository contains the source code for the manuscript "Experimental Interpretation of Adequate Weight-Metric Combination for Dynamic User-Based Collaborative Filtering" (short name is AdequateWeightMetricDynamicCF) by @savasokyay and @serco425
This repository holds my completed Octave/Matlab code for the exercises in the Stanford Machine Learning course, offered on the Coursera platform.
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