Books

Great software is built through great reviews. This book shows you how to spot hidden bugs, improve design, strengthen security, and review AI-generated code with confidence. Packed with practical examples and proven techniques, it helps you write better software in a world where humans and AI build code together.

Evaluation Engineering for AI Systems is a practical guide to building reliable AI evaluations for production. Learn how to measure performance, compare models, detect regressions and create evaluation pipelines using real-world examples, modern Python and proven industry practices.

An agent's answer can look right while its actions are wrong. Learn to evaluate tasks, traces, tool calls and changed state with reproducible harnesses, tested graders and regression gates.

Build a fully functional semantic search engine from first principles using pure Python and NumPy—no heavy AI frameworks, no vector databases, just pure intuition and mathematics.

AI can write code, create images and make decisions, but do you really understand what happens behind the scenes? This book cuts through the hype to explore how AI works, where it falls short and what it takes to build reliable systems. If you want to understand AI beyond the chat window, start with the code.

The model is one box. This book is about every other box: retries, contracts, evals, budgets, guardrails and agents for backend engineers shipping LLM features to production.

From Mathematical Foundations to the Future of AIMost deep learning still lives in flat, Euclidean space. Real-world data does not.This 15-chapter university textbook takes you from the basics of topology and geometry to the frontier of Geometric Deep Learning, Topological Data Analysis, equivariant networks, and optimization on manifolds.Clear explanations. Worked examples. Research roadmaps.

Build agents that write code, fix tests, and commit changes while you sleep — safely, cheaply, and entirely on your own hardware (622 manuscript pages).

AI can decide. That does not mean it is authorized to act. Governance Before Decision examines the missing control layer between intelligent systems and real-world consequences — where authority, scope, verification, and execution must meet.

What happens when AI moves beyond answering questions and begins to pursue goals?Agentic AI: The Rise of Autonomous, Goal-Driven Intelligence explores the emerging world of intelligent systems that can perceive, reason, plan, learn, collaborate, and act within defined environments.From the foundations of autonomous agents and multi-agent systems to robotics, finance, logistics, security, ethics, and future research, this book provides a structured journey through the rapidly evolving landscape of Agentic AI.Discover how goal-driven intelligence works, how autonomous agents make decisions, how multiple agents collaborate, and why safety, trust, accountability, and human oversight are essential to the future of autonomous systems.Understand the agents. Explore the architectures. Examine the applications. Think about the future.

Master AI/ML System Design with a Structured Interview FrameworkLearn how to approach complex ML system design interviews using a 20-step framework, architecture blueprints, real-world case studies, scalability strategies, data and model pipelines, deployment patterns, monitoring, and interview-ready templates.

Build Smarter Chatbots and Voice AssistantsExplore Conversational AI from fundamentals to real-world applications. Learn NLP, intent and context management, intelligent chatbots, voice assistants, speech technologies, multimodal interfaces, APIs, deployment, business integration, analytics, ethics, LLMs, and Generative AI.

Secure AI. Understand the Threats. Build More Trustworthy Intelligent Systems.Explore adversarial attacks, data poisoning, model theft, AI-enabled cyber threats, secure AI development, adversarial defenses, trustworthy AI, MLOps security, governance, privacy, red teaming, and the future of AI cybersecurity through practical concepts and real-world case studies.

Explore the Future of AI-Powered RoboticsDiscover how Artificial Intelligence is transforming robots into intelligent machines capable of learning, seeing, communicating, navigating, and making decisions. Explore Machine Learning, Computer Vision, NLP, Deep Learning, autonomous systems, smart factories, healthcare robots, drones, humanoids, agricultural robotics, ethics, and future trends.

A practical guide to evaluating small and local language models in the real world. Learn how to benchmark reliably, compare models across hardware and runtimes, optimize performance and avoid misleading results. With practical code and rigorous methods, you can build your own evaluation setup and make confident deployment decisions.