Session 11 Machine Learning: Text classification - Unsupervised (2)

Note: The following slides (Session 10) are material from a guest lecture presented by Camille Landesvatter (MZES Website).

• Learning outcomes:
  • learn basic concepts of Natural Language Processing (NLP)
  • become familiar with a typical (R-)workflow for text analysis
  • overview machine learning approaches for text data (supervised & unsupervised)
  • Lab:
    • Random forests for text classification