Word Embedding Techniques

Embedding techniques using in Natural Language Processing (NLP) to convert each Token(word) to an Word Embedding.


Notes:

  • Weighted Word representation: methods using TF-IDF to compute word values.
    • Distributional Representation: Words are stored based on their context, which is determined by how often they appear together and are stored in a word-context co-occurrence matrix.
  • Word Vectorization: