Artificial Intelligence is transforming how software is built, and Natural Language Processing (NLP) is at the center of this revolution.
Natural Language Processing with Transformers is a hands-on guide designed for developers who want to move beyond theory and start building real-world NLP applications using modern Transformer architectures.
Whether you're a Python developer, machine learning practitioner, data scientist, software engineer, or AI enthusiast, this book provides a practical path from foundational NLP concepts to production-ready Transformer systems.
Inside this book, you'll learn:
• How modern NLP evolved from traditional techniques to Transformer-based models
• The inner workings of attention mechanisms, embeddings, tokenization, encoders, and decoders
• How BERT, GPT, T5, BART, and other Transformer architectures operate
• Text classification, sentiment analysis, named entity recognition, and question answering
• Machine translation, text summarization, and semantic search systems
• Fine-tuning pre-trained models using the Hugging Face ecosystem
• Parameter-efficient training methods such as LoRA
• Building REST APIs, deploying models, and creating production-ready NLP applications
• End-to-end real-world projects that demonstrate practical implementation
With clear explanations, working code examples, practical exercises, and step-by-step guidance, this book bridges the gap between machine learning theory and professional NLP development.
By the end of this book, you will have the knowledge and confidence to build, fine-tune, deploy, and scale Transformer-powered applications for real-world use cases.
Perfect for developers looking to master the technologies driving modern AI and large language models.
