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Ramya Balakrishnan
Ramya Balakrishnan

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Jun 7, 2022

Different Techniques in Topic Modeling: LDA, Mallet LDA, STM & HDP

Different Techniques in Topic Modeling: LDA, Mallet LDA, STM & HDP In natural language processing, topic modeling is a type of statistical modeling that is used to discover abstract topics in a collection of documents. Though there are multiple techniques available in topic modeling implementation, evaluating the models has been…

6 min read

Different Techniques in Topic Modeling: LDA, Mallet LDA, STM & HDP
Different Techniques in Topic Modeling: LDA, Mallet LDA, STM & HDP

6 min read


Published in

Towards Data Science

·Apr 23, 2021

How to Make Topic Models Interpretable: 3 New Ideas

Three Innovative Techniques for Tuning LDA Topic Model Outputs — Topic modelling is an unsupervised machine learning approach which scans a set of documents, detects word and phrase patterns within them, and automatically clusters word groups and similar expressions that best characterize a set of text responses (or documents). To date, Latent Dirichlet Allocation (LDA) has been one of the…

Hands On Tutorials

6 min read

How to make Topic Models Interpretable: 3 New Ideas
How to make Topic Models Interpretable: 3 New Ideas
Hands On Tutorials

6 min read

Ramya Balakrishnan

Ramya Balakrishnan

9 Followers

Data Scientist at Center for Creative Leadership

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