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The Handbook of NLP with Gensim

You're reading from   The Handbook of NLP with Gensim Leverage topic modeling to uncover hidden patterns, themes, and valuable insights within textual data

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781803244945
Length 310 pages
Edition 1st Edition
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Author (1):
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Chris Kuo Chris Kuo
Author Profile Icon Chris Kuo
Chris Kuo
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Table of Contents (24) Chapters Close

Preface 1. Part 1: NLP Basics
2. Chapter 1: Introduction to NLP FREE CHAPTER 3. Chapter 2: Text Representation 4. Chapter 3: Text Wrangling and Preprocessing 5. Part 2: Latent Semantic Analysis/Latent Semantic Indexing
6. Chapter 4: Latent Semantic Analysis with scikit-learn 7. Chapter 5: Cosine Similarity 8. Chapter 6: Latent Semantic Indexing with Gensim 9. Part 3: Word2Vec and Doc2Vec
10. Chapter 7: Using Word2Vec 11. Chapter 8: Doc2Vec with Gensim 12. Part 4: Topic Modeling with Latent Dirichlet Allocation
13. Chapter 9: Understanding Discrete Distributions 14. Chapter 10: Latent Dirichlet Allocation 15. Chapter 11: LDA Modeling 16. Chapter 12: LDA Visualization 17. Chapter 13: The Ensemble LDA for Model Stability 18. Part 5: Comparison and Applications
19. Chapter 14: LDA and BERTopic 20. Chapter 15: Real-World Use Cases 21. Assessments 22. Index 23. Other Books You May Enjoy

Saving the model for production

There is one more thing we need to do before actually using the model. We need to save the following objects for future use:

  • The dictionary list
  • The model
  • The BoW object
  • The TF-IDF object

Let’s start by saving the dictionary list.

Gensim has a utility function called datapath. This is where we can specify the physical location of the file. Then, we can save the dictionary using the .save() function. Here is the code for it:

from gensim.test.utils import datapathdict_file = datapath(path + “/gensim_dictionary_AGnews”)
gensim_dictionary.save(dict_file)

Save the model as follows:

lsi_model.save(path + “/ag_news_lsi_model”)

Save the BoW object using pickle:

import picklefile = open(path + “/BoW_AGnews_corpus.pkl”, ‘wb’)
pickle.dump(bow_corpus, file)
file.close()

Save the TF-IDF object using pickle:

import picklefile = open(path + “/tfidf_AGnews_corpus...
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