Rank-based, collaborative filtering and matrix factorisation techniques for Recommendation Engine for IBM Watson Studio platform
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Updated
Feb 7, 2019 - HTML
Rank-based, collaborative filtering and matrix factorisation techniques for Recommendation Engine for IBM Watson Studio platform
Discovering latent features in restaurant reviews using Topic Modeling
A project for understanding latent spaces in different neural networks (joint work with interns 2018)
A C++ framework of Distributed Non-Negative Matrix Factorization implementation to find Latent Dimensionality in Big Data
musical snobbery, with a touch of machine learning
CP-APR Tensor Decomposition with PyTorch backend. pyCP_APR can perform non-negative Poisson Tensor Factorization on GPU, and includes an interface for anomaly detection using the extracted latent patterns.
Python Distributed Non Negative Matrix Factorization with custom clustering
Bayesian Factorization with Side Information in C++ with Python wrapper
scikit-fusion: Data fusion via collective latent factor models
Nimfa: Nonnegative matrix factorization in Python
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