Applied Natural Language Processing with PyTorch 2.0: Master Advanced NLP Techniques, Transform Text Data into Insights, and Build Scalable AI Models with PyTorch 2.0

Chopra, Dr. Deepti

ISBN 10: 9348107151 / ISBN 13: 9789348107152

Edité par Orange Education Pvt Ltd, 2025

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N° de réf. du vendeur 26403720566

Détails bibliographiques

• Titre: Applied Natural Language Processing with PyTorch 2.0: Master Advanced NLP Techniques, Transform Text Data into Insights, and Build Scalable AI Models with PyTorch 2.0
• Éditeur: Orange Education Pvt Ltd
• Date de parution: 2025
• Langue: anglais
• ISBN à 10 chiffres: 9348107151
• ISBN à 13 chiffres: 9789348107152
• Reliure: Couverture souple
• État de l'article: New

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Synopsis

Unlock the Power of PyTorch 2.0 for Next-Level Natural Language Processing.

Book Description
Natural Language Processing (NLP) is revolutionizing industries, from chatbots to data insights. PyTorch 2.0 offers the tools to build powerful NLP models. Applied Natural Language Processing with PyTorch 2.0 provides a practical guide to mastering NLP with this advanced framework.

This book starts with a strong foundation in NLP concepts and the essentials of PyTorch 2.0, ensuring that you are well-equipped to tackle advanced topics. It covers key techniques such as transformer models, pre-trained language models, sequence-to-sequence models, and more. Each chapter includes hands-on examples and code implementations for real-world application.

With a focus on practical use cases, the book explores NLP tasks like sentiment analysis, text classification, named entity recognition, machine translation, and text generation. You'll learn how to preprocess text, design neural architectures, train models, and evaluate results. Whether you're a beginner or an experienced professional, this book will empower you to develop advanced NLP models and solutions. Get started today and unlock the potential of NLP with PyTorch 2.0!

Table of Contents
1. Introduction to Natural Language Processing
2. Getting Started with PyTorch
3. Text Preprocessing
4. Building NLP Models with PyTorch
5. Advanced NLP Techniques with PyTorch
6. Model Training and Evaluation
7. Improving NLP Models with PyTorch
8. Deployment and Productionization
9. Case Studies and Practical Examples
10. Future Trends in Natural Language Processing and PyTorch
Index