nlp-zero-to-hero

Why we included this project

This one is for people who want a working mental model of NLP without hopping between scattered tutorials: the repo is a set of ten notebooks that build on each other in order, starting with tokenization and preprocessing, then moving through bag-of-words, TF-IDF, Naive Bayes classification, and topic modeling. From there it goes into word embeddings, RNNs, and attention, ending with the Transformer. Each step assumes the last, so you come away seeing how the field evolved and why modern approaches look the way they do. It suits data scientists and developers who already know some Python and want a structured, code-first introduction to core NLP concepts. The notebooks run in Google Colab or Kaggle, so you don't need a powerful local machine, and the progression leaves you with a solid base before moving on to production frameworks or large language models.