Natural Language Processing: Python and NLTK Training


Here you will learn to break down a text into its component parts for spelling correction, feature extraction, and phrase transformation. You will know simple and easy-to-comprehend programming formulae of NLP concepts. You can also be acquainted with several up-to-date and growing research topics regarding NLP. Finally, it can help you quickly master NLTK for natural language processing.
Natural Language Processing: Python and NLTK Training


  • Understand the complexity of natural language and how they machines manage the data
  • Familiarize yourself with sentiment analysis
  • Perform string matching algorithms and normalization techniques
  • Learn the concepts of information retrieval and text summarization


  1. Introduction to Natural Language Processing
  2. Text Wrangling and Cleansing
  3. Part of Speech Tagging
  4. Parsing Structure in Text
  5. NLP Applications
  6. Text Classification
  7. Web Crawling
  8. Using NLTK with Other Python Libraries
  9. Social Media Mining in Python
  10. Text Mining at Scale
  11. Tokenizing Text and WordNet Basics
  12. Replacing and Correcting Words
  13. Creating Custom Corpora
  14. Part-of-Speech Tagging
  15. Extracting Chunks
  16. Transforming Chunks and Trees
  17. Text Classification
  18. Distributed Processing and Handling Large Datasets
  19. Parsing Specific Data Types
  20. Working with Strings
  21. Statistical Language Modelling
  22. Morphology – Getting Our Feet Wet
  23. Parts-of-Speech Tagging – Identifying Words
  24. Parsing – Analyzing Training Data
  25. Semantic Analysis – Meaning Matters
  26. Sentiment Analysis – I Am Happy
  27. Information Retrieval – Accessing Information
  28. Discourse Analysis – Knowing is Believing
  29. Evaluation of NLP Systems – Analyzing Performance


Natural Language Processing: Python and NLTK Training

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