About
This comprehensive course on Natural Language Processing (NLP) is designed to take learners from zero knowledge to a working understanding of the subject. It covers fundamental concepts, techniques, and applications of NLP, providing hands-on experience with real-world data and tools. By the end of the course, learners will be equipped to implement NLP solutions and understand the latest advancements in the field. Table of contents Chapter 1: Introduction to NLP Chapter 2: Linguistic Fundamentals Chapter 3: Text Preprocessing Chapter 4: Regular Expressions Chapter 5: Bag-of-Words Model Chapter 6: TF-IDF (Term Frequency-Inverse Document Frequency) Chapter 7: Word Embeddings Chapter 8: Sentiment Analysis Chapter 9: Named Entity Recognition (NER) Chapter 10: Part-of-Speech Tagging Chapter 11: Text Classification Chapter 12: Topic Modeling Chapter 13: Machine Translation Chapter 14: Speech Recognition Chapter 15: Chatbots and Conversational Agents Chapter 16: Deep Learning for NLP Chapter 17: Transformer Models Chapter 18: Advanced NLP Techniques Chapter 19: NLP in Practice Chapter 20: Future of NLP