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Python Programming for Natural Language Processing A Step-by-Step Guide to Building

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Free Download Python Programming for Natural Language Processing: A Step-by-Step Guide to Building, Training, and Deploying NLP Models with Python, NLTK, and spaCy by Charlie J. Barrett
English | July 25, 2025 | ISBN: B0FK2T2DKQ | 194 pages | EPUB | 0.28 Mb
Are you tired of NLP tutorials that stop once the model is trained? Do you have the theoretical knowledge but struggle to turn your projects into tangible, production-ready products? Many developers learn the concepts but get stuck in the Jupyter Notebook, never making the leap to a live, scalable application. This book was written to break that cycle.​

This is not another academic textbook. Python Programming for Natural Language Processing is a hands-on, project-based guide that takes you on the complete journey from a raw text file to a deployed, containerized API on the cloud. We bridge the critical gap between data science theory and professional software engineering, using a modern, industry-standard toolkit including spaCy, Hugging Face Transformers, FastAPI, and Docker. You'll move beyond isolated scripts and learn the end-to-end workflow for building systems that work in the real world.
Imagine having the confidence and ability to not just analyze text, but to build applications that serve live predictions to users anywhere. After reading this book, you will have:Built and deployed a complete sentiment analysis classifier.Fine-tuned a state-of-the-art Transformer model for a custom classification task.Trained a custom Named Entity Recognition model to find domain-specific information.Packaged your model into a high-performance API with FastAPI.Containerized your application with Docker for ultimate portability.Deployed your NLP service to the cloud for the world to access.This book provides the practical, hard-won knowledge needed to become a confident and effective NLP engineer. If you're ready to stop just learning and start building, this is the guide you've been waiting for.

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