Natural Language Processing (NLP) – Text mining

CURRICULUM

  • NLP Resources,
  • Language as a probabilistic phenomenon
  • Zipf’s law, Word collocations
  • NLP and text retrieval basics
  • N-gram language models
  • Hidden markov model (HMM)
  • Part of speech tagging
  • Decision trees, Naive Bayes, Support Vector Machines
  • Feature selection schemes
  • Latent semantics and clustering problem
  • Introduction to Bayes nets and PGMs
  • Latent Dirichlet Allocation
  • Aspect extraction, Deception and Opinion spam
  • Topic Modelling
  • Word2Vec model
  • Text preprocessing
    ·         Noise Removal
    ·         Lexicon Normalization
  • Syntactical Parsing
  • Part of Speech Tagging
  • Entity Parsing
  • Phrase Detection
  • Named Entity Recognition
  • Topic Modelling
  • Lemmatization
  • N-Grams
  • Stemming
  • Text Matching
  • Levenshtein Distance

To buy this course mail us at info@myanalyticsmentor.com

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