NMF - Learn Data Science with Travis

Non-Negative Matrix Factorization (NMF) for Dimensionality Reduction in Image Data

Towards Data Science

Non-negative matrix factorization (NMF) is the process of decomposing a non-negative feature matrix, V (nxp) into a product of two non-negative matrices called W (nxd) and H (dxp). All three matrices ...

Topic Modeling with NMF for User Reviews Classification

Towards AI

A practical guide to using Non-Negative Matrix Factorization (NMF). A text mining technique to identify the topics of a document dataset and cluster them.

NMF — A visual explainer and Python Implementation

Towards Data Science

Gain an intuition for the unsupervised learning algorithm that allows data scientists to extract topics from texts, photos, and more, and build those handy recommendation systems. NMF explanation is…

Recommending Products with NMF

Towards AI

Intro Recommendation systems are all around us. Netflix uses them to show us movies and TV shows that we haven’t seen before, Pinterest uses them to show us ideas and pictures that we might be interes...

Practical Cython — Music Retrieval: Non Negative Matrix Factorisation

Towards Data Science

Welcome back to the Cython world :) This time I will show you how to implement a basic version of non-negative matrix factorisation (NMF). NMF has wide applications in data science¹ ² ³, music⁴ ⁵ and…...

Topic Modelling with NMF in Python

Towards AI

In the previous tutorial, we explained how we could apply LDA Topic Modeling with Gensim. Today, we will provide an example of Topic Modeling with Non-Negative Matrix Factorization (NMF) using…

Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation

Scikit-learn Examples

Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation This is an example of applying NMF and LatentDirichletAllocation on a corpus of documents and extract additive m...

Topic Modelling with NMF in Python

Python in Plain English

A practical example of Topic Modelling with Non-Negative Matrix Factorization in Python Continue reading on Python in Plain English

It’s NeRF or Nothin’!

Becoming Human: Artificial Intelligence Magazine

An introduction to Neural Radiance Fields and their applications What was done before NeRF? Deep Learning before this was essentially being performed a lot on 2D data, which is essentially what we ca...

Subword Techniques for Neural Machine Translation

Analytics Vidhya

Neural Machine Translation (NMT) is the current state-of-the-art machine translation technique which produces fluent translations. However, NMT models are affected by the Out of Vocabulary (OOV) and…

Predicting the Next Best Fantasy Football Team using the Non-negative Matrix Factorization Machine…

Towards Data Science

Using Machine Learning with NFL player stats helps you find the best Quarterback and Receiver Combinations. I used the NMF algorithm to do it.

Contextual Topic Modelling in Chinese Corpora with KeyNMF

Towards Data Science

A comprehensive guide on getting the most out of your Chinese topic models, from preprocessing to interpretation. With our recent paper on discourse dynamics in European Chinese diaspora media, our t...