BigARTM
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  • Introduction
  • Downloads
  • Installation
  • User’s Guide
    • Input Data Formats and Datasets
    • BigARTM Command Line Utility
    • Python Tutorial
    • Python Guide
      • 1. Loading Data: BatchVectorizer and Dictionary
      • 2. Base PLSA Model with Perplexity Score
      • 3. Regularizers and Scores Usage
      • 4. Multimodal Topic Models
      • 5. Phi and Theta Extraction. Transform Method
      • 6. Tokens Co-occurrence and Coherence Computation
      • 7. Attach Model and Custom Phi Initialization
      • 8. Deal with Ptdw Matrix
      • Different Useful Techniques
    • Regularizers Description
    • Scores Description
  • API References
  • VisARTM
  • Release Notes
  • BigARTM Developer’s Guide
BigARTM
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  • User’s Guide »
  • Python Guide
  • Edit on GitHub

Python Guide¶

  • 1. Loading Data: BatchVectorizer and Dictionary
  • 2. Base PLSA Model with Perplexity Score
  • 3. Regularizers and Scores Usage
  • 4. Multimodal Topic Models
  • 5. Phi and Theta Extraction. Transform Method
  • 6. Tokens Co-occurrence and Coherence Computation
  • 7. Attach Model and Custom Phi Initialization
  • 8. Deal with Ptdw Matrix
  • Different Useful Techniques
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