Topic Modelling in Semantic Embedding Spaces

Various examples of topic modeling and other text analysis

Latent Dirichlet Allocation coupled with Bayesian Time Series analyses

Collect Twitter data and create topic models with R

My version of topic modelling using Latent Dirichlet Allocation (LDA) which finds the best number of topics for a set of documents using ldatuning package which comes with different metrics

Structural Topic Modeling in R (published two articles on Medium). STM, LDA, metadata, NLP.

A rolling version of the Latent Dirichlet Allocation.

Optimal topic identification from a pool of Latent Dirichlet Allocation models

The repo contains the main topics carried out in my master's thesis on operational risk. In particular, it is described how to implement the so called Loss Distribution Approach (LDA), which is considered the state-of-the-art method to compute capital charge among large banks.

Determine a Prototype from a number of runs of Latent Dirichlet Allocation.

R codes for common Machine Learning Algorithms

Demonstration of a standard topic model approach

Protests and agitations have long used as means for showing dissident towards social, political and economic issues in civil societies. In recent years we have witnessed a large number of protests across various geographies. Not to be left behind by similar trends in the rest of the world, South Africa, in recent years have witnessed a large num…

Correlated topic modeling

Sign Language Digit Classification

Classic Machine Learning in R

Sequencing and interpreting multiple distribution signals

Word network topic modeling applied to short text

Topic model of curriculum of liberal arts program (with shiny app)

Introduction to Data Mining