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towardsdatascience.comVarious Implementations of Collaborative Filtering – Towards Data Science
Comparison of different methods to build recommendation system using collaborative filtering
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nipunbatra.github.ioNon-negative matrix factorisation using non-negative least squares
In this post, I will write about using non-negative least squares (NNLS) for the problem of non-negative matrix factorisation (NNMF).
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stackoverflow.comPython Non negative Matrix Factorization that handles both zeros and missing data?
I look for a NMF implementation that has a python interface, and handles both missing data and zeros.
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surpriselib.comSurprise - scikit for recommender systems
A simple Python library for building and testing recommender systems.
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docs.opencv.orgOpenCV: Introduction to Support Vector Machines
A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane.
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quora.comWhat is the meaning of low rank matrix? - Quora
A2A. Low rank matrix approximation is a widely used technique in Machine Learning. Perhaps, the best way to understand it would be through the classical item recommendation system example.
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pdfs.semanticscholar.orgLOW-RANK MATRIX FACTORIZATION
LOW-RANK MATRIX FACTORIZATION FOR DEEP NEURAL NETWORK TRAINING WITH HIGH-DIMENSIONAL OUTPUT TARGETS
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ismll.uni-hildesheim.deFactorized Polynomial Regression Models
Factorization Machines (FM) are a new model class that combines the advantages of polynomial regression models with factorization models
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quora.comWhat are factorization machines and how are they used in machine learning?
Here are some basic facts about factorization machines (FM)
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github.comgeffy/tffm
tffm - TensorFlow implementation of an arbitrary order Factorization Machine
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getstream.ioFactorization Machines for Recommendation Systems | The Stream Blog
FM models have enough expressive capacity to generalize methods such as Matrix/Tensor Factorization and Polynomial Kernel regression.
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github.comscikit-learn-contrib/polylearn
polylearn - A library for factorization machines and polynomial networks for classification and regression in Python.
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github.comibayer/fastFM
fastFM: A Library for Factorization Machines
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securityintelligence.comFactorization Machines: A New Way of Looking at Machine Learning
Here's a look at Steffen Rendle's theory on factorization machines — including how they could be used to assist data scientists in the future.
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libfm.org
libFM - Factorization Machine Library
Factorization machines (FM) are a generic approach that allows to mimic most factorization models by feature engineering. This way, factorization machines combine the generality of feature engineeri
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libfm.orglibFM 1.4.2
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algo.uni-konstanz.deFactorization Machines
In this paper, we introduce Factorization Machines (FM) which are a new model class that combines the advantages of Support Vector Machines (SVM) with factorization models.
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lineardigressions.comFactorization Machines
What do you get when you cross a support vector machine with matrix factorization? You get a factorization machine, and a darn fine algorithm for recommendation engines.
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