Statistical Markov Language Models

• are based on counting of words and
• are precursor to modern word embeddings such as Word2Vec,

• Before attempting the best-in-class Language models (pre-trained or otherwise) that involve seq2seq networks and transformers, I wanted to take a step back and understand the fundamentals better
• That is the reason behind developing codes and notes for Bigram and Trigram Markov Language Models.
• The below link has my notes on Statistical Markov Language Models:
  https://senthilkumarm1901.github.io/StatisticalLanguageModels/