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Natural Language Processing with Python: Build Real-World NLP Applications Using NLTK, spaCy, and Transformers
Paperback
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ISBN13: 9798296311412
Publisher: Independently Published
Published: Aug 2 2025
Pages: 222
Weight: 0.87
Height: 0.47 Width: 7.00 Depth: 10.00
Language: English
Publisher: Independently Published
Published: Aug 2 2025
Pages: 222
Weight: 0.87
Height: 0.47 Width: 7.00 Depth: 10.00
Language: English
Natural Language Processing with Python: Build Real-World NLP Applications Using NLTK, spaCy, and Transformers This hands-on guide takes you on a practical journey into the world of Natural Language Processing (NLP) using Python. Whether you're a beginner or looking to enhance your skills, this book equips you with the tools and techniques to build real-world NLP applications using the most popular libraries: NLTK, spaCy, and Hugging Face Transformers. From foundational text processing to cutting-edge deep learning models, you'll learn how to preprocess, analyze, and understand text in meaningful ways.
Covering everything from tokenization and named entity recognition to fine-tuning transformer models like BERT and GPT, the book blends theory with real implementation. You'll work through complete projects such as text classification, sentiment analysis, question answering, and language generation making it easy to apply what you learn directly to real use cases.
Natural Language Processing with Python bridges the gap between theory and practice by guiding readers through essential NLP workflows using three powerful libraries. You'll master the basics with NLTK, streamline processes with spaCy, and tap into state-of-the-art AI using Hugging Face Transformers. The book is structured to build your confidence from the ground up starting with core preprocessing tasks and culminating in the deployment of modern NLP applications. Key Features of This Book:
Natural Language Processing with Python bridges the gap between theory and practice by guiding readers through essential NLP workflows using three powerful libraries. You'll master the basics with NLTK, streamline processes with spaCy, and tap into state-of-the-art AI using Hugging Face Transformers. The book is structured to build your confidence from the ground up starting with core preprocessing tasks and culminating in the deployment of modern NLP applications. Key Features of This Book:
- Step-by-step tutorials for practical NLP tasks using real datasets
- In-depth exploration of NLTK, spaCy, and Transformers
- Full projects on text classification, summarization, and more
- Clear explanations with annotated code examples
- Guidance on deploying NLP models with FastAPI or Flask
- Best practices for evaluating model performance and mitigating bias
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