PART-3: Natural Language Processing (NLP)

14. Introduction to Natural Language Processing

  • NLTK, SPACY and built-in CORPUS

  • The Bag-of-words strategy

    • Tokenizing

      • Sentence Tokenization

      • Word Tokenizing

    • Stopwords removal

      • Language Detection

    • Stemming

    • Vectoring

      • Count Vectorizing

      • Uni-gram, Bi-gram, N-gram

      • Tf-IdfVectorizing

  • A sample text classifier based on the Reuters Corpus

15. Topic Modeling and Sentiment Analysis in NLP

  • Topic Modelling

  • Latent semantic analysis

  • Probabilistic latent semantic analysis

  • Latent Dirichlet Allocation (LDA)

  • Sentiment Analysis

    • VADER sentiment analysis with NLTK

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