Mastering NLP Systems in Python: A Hands-On Guide with Neural Networks
Practical Deep Learning and AI Techniques for Real-World Language Applications
This book is a comprehensive, practice-oriented guide for developers, data scientists, and AI enthusiasts eager to build powerful Natural Language Processing (NLP) systems using Python. From the fundamentals of text preprocessing to advanced deep learning architectures, readers will gain the skills needed to design, train, and deploy neural-network-driven NLP models for real-world applications.
Through hands-on examples and step-by-step tutorials, the book explores:
Core NLP concepts such as tokenization, embeddings, and sequence modeling.
Building neural networks with TensorFlow and PyTorch for tasks like sentiment analysis, machine translation, and text generation.
Applying transformer architectures (e.g., BERT, GPT) to achieve state-of-the-art results.
Best practices for preparing datasets, optimizing models, and scaling systems for production.
Real-world projects that bridge the gap between theory and practical deployment.
Whether you are a beginner entering the world of NLP or an experienced practitioner looking to expand your deep learning expertise, this book provides the tools, techniques, and insights to master modern NLP systems with confidence.


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