The Transformer Architecture : AI Revolution

This text of this book "The Transformer Architecture : AI Revolution" is structured to cater to a wide audience, from undergraduate (B.Tech) students taking their first steps into deep learning to postgraduate (M.Tech) scholars and professionals seeking to master the state-of-the-art. We start with the foundational building blocks, assuming only a basic knowledge of programming and machine learning, and progressively build up to advanced concepts like BERT, GPT, and Vision Transformers. Every chapter is a stepping stone, designed to build your confidence and competence.

Key Features of This Book:


1. Beginner to Advanced Progression: The book is structured to guide learners smoothly from the basics of sequential models to the complexities of advanced architectures like BERT, GPT, and Vision Transformers.
2. Hands-On Practicals: Almost every chapter includes hands-on coding examples and mini-projects using popular Python libraries like PyTorch, TensorFlow, and Hugging Face Transformers.
3. Intuition-First Explanations: We prioritize building a strong conceptual understanding with real-life analogies and clear diagrams before diving into the mathematical details.
4. Real-World Use Cases: Learn how Transformers are applied in sentiment analysis, machine translation, text generation, question answering, and even image recognition, connecting theory to industry practice.
5. Complete Capstone Project: The final chapter provides a detailed, step-by-step guide to building a fully functional, fine-tuned conversational AI, complete with all the necessary code and explanations.
6. Updated and Relevant Content: The book covers the latest and most influential models, ensuring you learn the concepts that are driving the industry today and will shape it tomorrow.
7. Focus on Foundational Skills: By understanding the core mechanics of the Transformer, you will be equipped to understand and adapt to future architectures that build upon its principles.
8. NEP 2020 & AICTE Compliant: The content promotes skill-based learning, critical thinking, and a project-based approach, directly aligning with modern educational frameworks.


Without it, the current AI landscape would be unrecognisable.