Topic Modeling Workshop for Beginners in Python

Topic Modeling Workshop for Beginners in Python

Prodramp via YouTube Direct link

- Step 2.1: Removing Punctuation

11 of 27

11 of 27

- Step 2.1: Removing Punctuation

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Classroom Contents

Topic Modeling Workshop for Beginners in Python

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  1. 1 - Tutorial Starts
  2. 2 - Topic Modeling Intro
  3. 3 - Workshop Environment
  4. 4 - Content location at GitHub
  5. 5 - Dataset used in this workshop
  6. 6 - LDA Intro
  7. 7 - Topic Modeling Use Cases
  8. 8 - 6 Steps in this Workshop
  9. 9 - Step 1: Loading Data
  10. 10 - Step 2: Data Preparation
  11. 11 - Step 2.1: Removing Punctuation
  12. 12 - Step 2.2: Removing digits and word with digits
  13. 13 - Step 2.3: Lowercase all context
  14. 14 - Step 3: EDA
  15. 15 - Step 3.1: Word Cloud
  16. 16 - Step 3.2: Document Term Matrix
  17. 17 - Step 4: Data Modeling
  18. 18 - Step 4.1: Stop words removal
  19. 19 - Step 4.2: Creating Bigram and Trigram
  20. 20 - Step 4.3: Lemmatization
  21. 21 - Step 4.4: Tokenization
  22. 22 - Step 5: LDA Topic Modeling
  23. 23 - Step 6: Topic Modeling Performance and analysis
  24. 24 - Step 6.1: Topic visualization
  25. 25 - Step 6.2: Coherence Score
  26. 26 - Saving notebook to GitHub
  27. 27 - Recap

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