Everything about Language Models And AI Agents-

Everything about Language Models And AI Agents: The Intuition, Internals and Implementation

₹1,100.00

  • By: M K Pavan Kumar
  • ISBN: 9789376866328
  • Price: 1100/-
  • Page: 365
  • Size: 6×9
  • Category: EDUCATION / General
  • Language: English
  • Delivery Time: 07-09 Days
Category: Tags: ,

Description

About The Book

This book is a comprehensive, end-to-end guide that bridges theory and real-world practice in modern AI systems. It is structured to help readers move from foundational understanding to building production-ready applications.
At its core, the book focuses on three layers. The first is intuition, where complex ideas like transformers, embeddings, and generative behavior are broken down into clear mental models. Instead of treating language models as black boxes, it builds a strong conceptual base so readers can reason about how and why these systems work.
The second layer dives into internals. Here, you explore the mechanics of tokenization, attention, training dynamics, inference optimization, and architectural choices behind large language models. It also connects these ideas to practical concerns such as latency, cost, and scalability, which are critical when deploying systems in real environments.
The final layer is implementation. This is where the book stands out. It goes beyond explanations and shows how to build AI agents, retrieval-augmented systems, memory-driven architectures, and tool-using agents. Readers learn how to integrate models into workflows, design robust pipelines, and evaluate system performance effectively.
Overall, the book is both a learning resource and a builder’s handbook. It is designed for engineers, researchers, and practitioners who want not just to understand language models, but to use them confidently in real-world applications.

About The Author 

M K Pavan Kumar is a Distinguished AI Architect with deep expertise in Generative AI and large language models. With over 15 years of experience in the technology industry, he has worked across domains such as ERP, insurance, and aerospace, building scalable and production-grade systems that solve real-world problems.

He holds a dual master’s degree, including a Master of Computer Applications from Osmania University and a Master’s in Data Science from BITS Pilani. His work focuses on bridging the gap between theory and implementation, enabling organizations to effectively design, deploy, and optimize AI-driven solutions.

Pavan is the creator of QQL, a query language designed to bring a SQL-like experience to vector search, making retrieval systems more intuitive and developer-friendly. He has also contributed to projects such as Bootstrap RAG and CodeEvals, reflecting his interest in advancing retrieval-augmented generation and evaluation frameworks.

An active open-source contributor and technology evangelist, Pavan has authored over 200 technical blogs spanning data engineering, artificial intelligence, and modern AI systems. He is also a Distinguished Ambassador for Qdrant, where he contributes to the growing ecosystem around vector databases and semantic search.

Through his work, writing, and community involvement, Pavan continues to help practitioners move beyond understanding AI concepts to building impactful, real-world applications.

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