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Re-Imagining Topic Modeling in NLP: A Break from Conventional Approach
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Timestamps:
00:00 Topic introduction
01:25 Speaker Introduction
02:34 What is Topic Modelling?
03:11 The Conventional Approach
04:08 Flaws in LDA
05:00 Contextual Topic Modelling
06:12 Entity Recognition + Collocations
06:44 Data Pipeline
07:18 The Flow
08:26 Insights and Visualisations
10:26 Comparing Conventional & Contextual Topic Modelling
11:26 Limitations of Contextual Topic Modelling NER Collocations
12:19 Future Opportunities & Use Cases
La Kopi @ Developers Space is a monthly open mic night for the developer community to learn, connect, and be inspired by each other. Every month, a tech theme is selected and developers submit their topics to be shared with the community.
Name: Shubhanshu Gupta (Machine Learning Engineer, Citibank)
Topic: Re-Imagining Topic Modeling in NLP: A Break from Conventional Approach
When it comes to topic modeling, most of the NLP practitioners use LDA (Latent Dirichlet Allocation) or LSA (Latent Semantic Analysis). While there's nothing wrong with any of the approaches, it's certainly possible to challenge the convention and think outside the box.
This talk presents a new way to approach and think about mining topics from your text data. Shubhanshu will walk you through an example using Named Entity Recognition and Collocations, which yields high quality, meaningful and intuitive topics and visualizations.
For more updates on upcoming events, follow us on social media:
00:00 Topic introduction
01:25 Speaker Introduction
02:34 What is Topic Modelling?
03:11 The Conventional Approach
04:08 Flaws in LDA
05:00 Contextual Topic Modelling
06:12 Entity Recognition + Collocations
06:44 Data Pipeline
07:18 The Flow
08:26 Insights and Visualisations
10:26 Comparing Conventional & Contextual Topic Modelling
11:26 Limitations of Contextual Topic Modelling NER Collocations
12:19 Future Opportunities & Use Cases
La Kopi @ Developers Space is a monthly open mic night for the developer community to learn, connect, and be inspired by each other. Every month, a tech theme is selected and developers submit their topics to be shared with the community.
Name: Shubhanshu Gupta (Machine Learning Engineer, Citibank)
Topic: Re-Imagining Topic Modeling in NLP: A Break from Conventional Approach
When it comes to topic modeling, most of the NLP practitioners use LDA (Latent Dirichlet Allocation) or LSA (Latent Semantic Analysis). While there's nothing wrong with any of the approaches, it's certainly possible to challenge the convention and think outside the box.
This talk presents a new way to approach and think about mining topics from your text data. Shubhanshu will walk you through an example using Named Entity Recognition and Collocations, which yields high quality, meaningful and intuitive topics and visualizations.
For more updates on upcoming events, follow us on social media:
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