Books

Linear Programming and AI Optimization Models (VOL-3) delivers practical mastery in scheduling, supply chain, logistics, hybrid AI-OR systems, large-scale cloud optimization, and emerging technologies. With Python implementations, industry case studies, and forward-looking research trends, this volume turns theory into powerful real-world solutions.

Take your optimization skills to the next level with AI.Linear Programming and AI Optimization Models (VOL-2) dives deep into the algorithms driving modern Machine Learning and Intelligent Systems. Master Gradient Descent, Adam, Reinforcement Learning, Genetic Algorithms, Particle Swarm Optimization, Constraint Satisfaction, and advanced Network Models.

Anyone can run INT4 and read off the accuracy drop. This book explains why that number is what it is — building every quantization method from scratch, breaking it on purpose, and measuring the result. Quantization, from the bits up.

Build real-world AI applications with Python—not just demos. Learn LLM APIs, RAG, embeddings, vector search, AI agents, prompt engineering, security, deployment, and production-ready architectures through practical projects and expert guidance. Gain the skills to build, ship, and scale modern AI systems with confidence.

Learn Python from scratch with this clear, step-by-step beginner’s guide. Perfect for students, professionals, and self-learners. Master programming fundamentals through practical examples, exercises, and real mini-projects. Build confidence and start coding today!

Master DeepSeek V3 — one of the most capable AI models of its time.This practical guide teaches students, researchers, and professionals how to use DeepSeek V3 for learning, research, coding, content creation, automation, and productivity — with strong focus on prompt engineering and responsible AI usage.

How does code actually run under the hood? Stop guessing and master the hidden physics of execution. Learn how Python and Java truly manage memory, layout data structures, and drive high-performance algorithms.

From LLMs and RAG to Memory, MCP, Agent Frameworks and Enterprise AI Controls—discover how modern AI Agents work internally within today's rapidly evolving AI ecosystem.

Every web application has security headers, cookies, TLS configurations, and CORS policies that need to be correct. Most teams find out they're wrong only after a penetration test — or worse, after an incident. This book shows you how to build a scanner that catches these issues automatically. You'll create a Python CLI tool that uses Hurl (declarative HTTP testing) to assert security properties, SSLyze to validate TLS protocol versions, and AI to generate specific remediation for every failure it finds. The output: structured JSON reports, visual HTML dashboards, and AI-generated security posture assessments. **What you'll build:** - 9 declarative Hurl security test files (headers, cookies, CORS, HSTS, CSP, CSRF, redirects, TLS) - A preprocessor that handles domain substitution and authentication - An output parser with built-in remediation guidance for every test - A TLS scanner validating SSL 2.0/3.0 disabled and TLS 1.2/1.3 enabled - An AI analyzer that generates context-specific fixes using Ollama, OpenAI, or Bedrock - An HTML reporter with dark-themed visual dashboards - Docker multi-architecture deployment - CI/CD pipeline with GitHub Actions **Who this is for:** - Developers who want security checks before deploying - DevSecOps engineers building CI/CD security gates - Penetration testers who need quick baseline assessments - Security students learning web vulnerability concepts hands-on - Platform teams enforcing security standards across services Every failure includes: what was expected, what was received, why it matters, how to fix it, and a documentation link. AI adds domain-specific code examples on top.

Threat modeling is broken. It takes days, costs thousands, and most teams skip it entirely. What if your AI coding assistant could do it for you — systematically, consistently, and in minutes? This book shows you how to build an MCP server that makes it happen. You'll create 80+ structured tools that guide any AI assistant through a rigorous 9-phase STRIDE threat modeling workflow. Not vague prompts that produce unstructured text — real, typed, validated tools that build up a complete threat model piece by piece: business context, architecture, threat actors, trust boundaries, data flows, STRIDE-based threats, mitigations, and a final JSON export compatible with AWS Threat Composer. **What you'll build:** - A full MCP server with FastMCP (stdio + SSE transport) - Pydantic v2 data models for type-safe threat modeling - Case-insensitive enum validation (because AI isn't always consistent) - 11 tool modules covering every phase of STRIDE analysis - Customizable organization security guidelines loaded from `.md` files - Docker deployment for team-wide access - Compliance gap analysis that validates against mandatory controls - A complete workflow orchestrator with progress tracking **What makes this different:** The server doesn't call any LLM itself. It provides the structure and tools — your AI assistant (Claude, Kiro, Cursor, Copilot) provides the intelligence. This means it works with any model, any provider, forever. No API keys, no token costs for the server itself. **Who this is for:** - Security engineers who want to automate repetitive threat modeling - Python developers building MCP servers for any domain - DevSecOps teams embedding security into AI-assisted workflows - Architects who need consistent, auditable threat models - Anyone curious about how MCP tools work under the hood **By the end of this book**, you'll have a production-ready MCP server, a deep understanding of how AI tools are structured, and transferable patterns for building MCP servers in any domain — not just security.

Have you ever wondered how AI knows that "Which company designs iPhone?" is best answered by "Apple designs iPhone" — and not "I love to eat apple" or "Both Apple and Orange are fruits"? This book takes you on a visual, step-by-step journey to discover how artificial intelligence reads the meaning behind words — not just the words themselves. By the end, you'll understand the elegant idea powering modern AI chatbots, and write your own Python programs to find the best answer to any question from a list of sentences.

# 🚀 Master the Math Behind Artificial Intelligence!Stop drowning in complex textbooks. This premium, high-density **AI Math Cheat Sheet** is engineered specifically for Data Scientists, ML Engineers, and Python Developers who want to bridge the gap between mathematical theory and production-ready co

A practical guide to operating a fleet of AI coding agents through routing, memory, skills, MCP, guardrails, and a persistent control plane (286 manuscript pages).

Stop guessing the math behind AI and start coding it. This practical guide bridges the gap between complex formulas and real-world Python implementation, giving you the exact blueprint to master the algorithms powering modern machine learning.

Want to learn Python from the ground up and master its real-world applications?Python Programming: Basics to Advanced Concepts is your complete guide to one of the world's most powerful and versatile programming languages. Whether you are a BCA or MCA student, an aspiring software developer, a competitive examination candidate, or a technology enthusiast, this book provides a structured learning path from Python fundamentals to advanced programming techniques.Inside this book, you will learn:✔ Python syntax, variables, data types, and operators✔ Conditional statements, loops, and functions✔ Lists, tuples, dictionaries, sets, and strings✔ Object-Oriented Programming (OOP)✔ Exception handling and file management✔ Modules, packages, generators, and decorators✔ Database programming with SQLite and MySQL✔ GUI development using Tkinter✔ Web development with Flask and Django✔ Data analysis using NumPy and Pandas✔ Machine Learning fundamentals with Python✔ Network programming and cybersecurity applications✔ Testing, debugging, and performance optimization✔ End-to-end Python project developmentThe book combines academic rigor with practical learning, offering clear explanations, coding examples, exercises, and real-world applications throughout every chapter.Whether your goal is to excel in university examinations, prepare for interviews, build software projects, or launch a professional programming career, this book provides the knowledge, skills, and confidence required to become a proficient Python developer.Start your Python journey today and unlock opportunities in software development, data science, artificial intelligence, cybersecurity, automation, and beyond.