LDA Topic Models
LDA Topic Models is a powerful tool for extracting meaning from text. In this video I talk about the idea behind the LDA itself, why does it work, what are the free tools and frameworks that can be used, what LDA parameters are tuneable, what do they mean in terms of your specific use case and what to look for when you evaluate it.
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Latent Dirichlet Allocation (Part 1 of 2)
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An Introduction to Topic Modeling
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Matti Lyra - Evaluating Topic Models
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Computational Linguistics I: Topic Modeling
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BERTopic for Topic Modeling - Maarten Grootendorst - Talking Language AI Ep#1
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Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python
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LDA Topic modeling in R
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When an audition changed TV forever
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Judge Can’t Stop Laughing At Sovereign Citizen’s Courtroom Meltdown!!!
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Hierarchical Topic Modeling in Cancer Research - Zhi Yang - ML4ALL 2019
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BERTopic Explained
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Topic Models: Introduction
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Prof. David Blei - Probabilistic Topic Models and User Behavior
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Topic modeling with R and tidy data principles
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Nonparametric Bayesian Methods: Models, Algorithms, and Applications I
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Word Embeddings
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Topic Models
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NLP Demystified 9: Automatically Finding Topics in Documents with Latent Dirichlet Allocation
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LDA Topic Modelling Explained with implementation using gensim in Python #nlp #tutorial
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