Machine learning in NLP

This document contains the practical use cases in my daily NLP projects.

• Data cleaning
  • Clean text with regex
  • Clean text with NLTK
  • Text cleaning pipeline
  • Text cleaning module
• Text vectorization
  • Bag of words
  • N-gram vectorizer
  • Tfidf vectorizer
  • Customized vectorizer
• Feature engineering
  • Dimension reduction
  • Feature extraction
• Embeddings
  • Word embedding
  • Document embedding
• Machine learning models - Tree-based
  • Model selection
  • Model evaluation
• Machine learning models - Neural networks
• Machine learning models - Recurrent Neural Networks
• Machine learning models - BERT
  • Background
  • Codes
• Metrics
  • Classification
  • Regression
  • Learn to Rank (Recommender systems)