A collection of notes learned from the book Practical Natural Language Processing. You can find original jupyter notebook of this book in this repository.
- Chapter 02: NLP Pipeline
- Chapter 03: Text Representation
- Chapter 04: Text Classification
- One Pipeline Many Classifiers
- Word Embeddings
- Deep Learning for Text Classification
- Text Classification with Large Pre-Trained Language Model
- Lime and SHAP
- Learning with No or Less Data with Case Study
- Chapter 05: Information Extraction
- Information Extraction
- Keyphrase Extraction (KPE)
- Named Entity Recognition (NER)
- Named Entity Disambiguation and Linking
- Relationship Extraction
- Other Advanced IE Tasks and Case Study
- Chapter 06: Chatbots
- Chapter 07: Topics in Brief
- Search and Information Retrieval (Elastic Search)
- Topic Modeling
- Text Summarization
- Recommender Systems
- Machine Translation
- Question Answering Systems
- Chapter 08: Social Media
- Chapter 09: E-Commerce and Retail
- Chapter 10: Healthcare, Finance, and Law
- Heatlhcare
- Finance and Law
- Chapter 11: The End-to-End NLP Process
