SKILL BENCHMARK

Natural Language Processing: Text Mining and Analytics Competency (Intermediate Level)

  • 7m
  • 7 questions
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The Text Mining and Analytics Competency (Intermediate Level) benchmark measures your experience with natural language processing (NLP) techniques and tools, such as text mining and analytics, spaCy, NLTK, libraries and frameworks for app development, and sentiment analysis. Learners who score high on this benchmark demonstrate that they have a good working knowledge of natural language processing text mining and analytics and can work on NLP text analytics projects with minimal supervision.

Topics covered

  • demonstrate the lexical resource for opinion mining and finding the sentiment of text
  • demonstrate the Python RE Module, RE - Search, Find ALL, Finditer, Groups, Find and Replace, and Split
  • illustrate and extract synonyms and identify WordNet hierarchies - hypernyms and hyponyms
  • model and find sentiment of movie plots using SentiWordNet
  • outline the heuristic approach for natural language processing (NLP)
  • perform advanced information extraction using NLTK chunking and regex rules
  • perform basic information extraction using NLTK chunking and regex rules