Book Description
Natural Language Processing (NLP) is at the core of modern AI, powering everything from chatbots to recommendation systems. “Ultimate Natural Language Processing with spaCy and Hugging Face” is a practical guide that takes you from essential NLP foundations to advanced transformer models and large language applications, equipping you to build real-world AI projects with confidence.

You begin with the fundamentals—tokenization, lemmatization, Bag-of-Words, TF-IDF, embeddings, POS tagging, and Named Entity Recognition—and apply them to practical use cases such as sentiment analysis, topic classification, and text classification.

The book then moves into Deep Learning for NLP with hands-on coding of CNNs, RNNs, and LSTMs, progressing from theory to applied projects. spaCy is explored in depth, with guidance on building and customizing pipelines for NER, POS tagging, and sentiment analysis. Real-world projects, including extracting dates and events from news articles, ensure that every concept connects to practical applications.

Table of Contents
1. Introduction to NLP and the Essential Libraries
2. Building Blocks and Techniques for NLP Algorithms
3. Sentiment Analysis Using NLP
4. Deep Learning in NLP
5. Working with CNN
6. Building NLP Pipelines Using spaCy
7. Building a spaCy Pipeline for Extracting Information
8. Building a Transformer Using Hugging Face
9. Training Language Models
10. Importance of Large Language Models and Their Applications
11. Fine-Tuning LLMs and Building Text-Powered Tools
12. Best Practices and Future Trends of NLP
Index