A comprehensive, vendor-neutral documentation project covering Natural Language Processing from traditional methods through modern Large Language Models — structured for practitioners, students, and researchers.
- Part I: Traditional NLP — text preprocessing, feature engineering, text similarity, syntax and parsing, semantics and pragmatics, corpus linguistics, speech processing
- Part II: Modern NLP — word embeddings, sequence models, CNNs, attention mechanisms, transfer learning
- Part III: Large Language Models (LLMs) — Transformer architectures, encoder/decoder families, multimodality, decoding, compression, training, and inference
- Part IV: Applied LLM Engineering — prompting, RAG and retrieval, agents, tool calling, data lifecycle, long context, memory, and guardrails
- Part V: Evaluation, Safety, Ethics & Governance — metrics, hallucinations, bias, privacy, interpretability, agent security, accessibility, sustainability, and governance
- Part VI: Practitioner's Guide — ecosystem libraries, model selection, development best practices, production deployment
- Part VII: Mathematical Foundations — probability and information theory, vector algebra, transformer math
- Part VIII: Appendix & References — glossary, abbreviations, further reading, landmark papers
- Parts IX-XII — best practices, templates, checklists, and labs
- FAQ and License — common questions, contribution guidance, and content licensing
Requires Node.js 20 or newer.
# Install dependencies
npm install
# Start the development server
npm start
# Build for production
npm run build
# Run documentation checks and the production build
npm run validateProduction builds generate sitemap.xml with the official @docusaurus/plugin-sitemap for search-engine discovery. Local full-text search is provided by @easyops-cn/docusaurus-search-local.
Documentation content in this repository is provided under the Creative Commons Attribution 4.0 International license (CC BY 4.0), except where third-party rights apply.