Books

Move beyond AI demos and build agents that can actually run IT operations. This practical guide takes you from MCP fundamentals to production-ready monitoring, incident response, remediation, Kubernetes operations, security and multi-agent systems, with complete runnable code and a strong focus on safe autonomy.

Cyber threats do not stop at the office network. When industrial systems are targeted, the consequences can reach far beyond lost data. This practical guide shows how to secure OT and critical infrastructure from the ground up, combining proven standards, real-world defenses and hands-on guidance for the systems that keep the world running.

A cinematic, hybrid‑illustrated survival guide featuring eight printable wallet‑size reference cards. Includes knots, fire‑starting basics, emergency signals, navigation, packing essentials, and lost/stranded protocols.

门禁、支付、定位、摄像和个人 AI 都证明她到过命案现场。她必须先证明，这五个证人从来不是五个。

A cinematic, illustrated sustainability guide designed for beginners, renters, families, and small‑space homes. Includes eco habits, reusable swaps, composting options, home audits, energy optimization, renter‑friendly upgrades, and a 7‑day activation plan.

Build powerful web applications with Python and Django.Django is one of the most capable frameworks for building modern web applications, but mastering it requires more than learning a few commands. You need to understand its architecture, database layer, request-response cycle, security model, APIs, testing practices, performance techniques, and deployment workflow.Django Unleashed: Building High-Performance Web Applications with Python provides a practical roadmap for developing Django applications from the ground up.Starting with Django fundamentals, you will learn how projects and applications are structured, how URLs connect requests to views, how templates generate dynamic interfaces, and how Django's ORM communicates with databases.The book then moves into models, QuerySets, relationships, forms, validation, authentication, authorization, static files, and media handling.A dedicated section on Django REST Framework introduces REST APIs, serializers, APIViews, ViewSets, routers, authentication, CRUD operations, filtering, pagination, and testing. You will also explore frontend integration using HTML, CSS, JavaScript, AJAX, React, and Vue.js.As your skills develop, the book introduces professional development practices including automated testing, CI/CD, security hardening, database optimization, caching, Redis, Memcached, Celery, profiling, and application scaling.The deployment chapters explain how to prepare Django applications for production and work with technologies such as Nginx, Gunicorn, HTTPS, AWS, DigitalOcean, and Heroku.With practical examples, troubleshooting guidance, real-world development concepts, and a comprehensive reference section, this book is designed to help you move from learning Django to building applications that are ready for real-world use.Learn Django. Build applications. Secure your code. Optimize performance. Deploy with confidence.

Statistics is the language of uncertainty. AI is the science of learning from data. Together, they provide a powerful foundation for modern intelligent systems.Applied Statistics with AI: Hypothesis Testing and Inference for Modern Models is designed for learners who want to understand how statistical methods can be applied to Artificial Intelligence, Machine Learning, Data Science, and modern research.The book begins with essential statistical foundations, including data types, sampling, preprocessing, descriptive statistics, visualization, probability, and probability distributions. It then builds toward statistical inference, covering estimation, Maximum Likelihood Estimation, Bayesian estimation, hypothesis testing, p-values, confidence intervals, Type I and Type II errors, and statistical significance.Readers will learn how classical statistical tests such as t-tests, ANOVA, and Chi-Square tests can be used in AI-related contexts, along with non-parametric methods such as Wilcoxon, Mann-Whitney, Kruskal-Wallis, and Kolmogorov-Smirnov tests.The book then connects statistics directly to Machine Learning through regression, model evaluation, cross-validation, resampling, feature selection, PCA, regularization, A/B testing, and statistical power.Advanced chapters explore Bayesian inference, MCMC, causal inference, uncertainty quantification in deep learning, and confidence estimation in AI predictions. Real-world case studies demonstrate how statistical inference can support applications in healthcare, finance, Natural Language Processing, and Computer Vision.The book also addresses an increasingly important dimension of AI: responsible statistical practice. Readers will explore bias detection, fairness, ethical hypothesis testing, and the responsible interpretation of AI research results.Finally, the book looks ahead to automated statistical inference, AI-driven hypothesis generation, and emerging research challenges.Whether you are a student learning statistics for AI, a researcher evaluating machine learning experiments, a data scientist analyzing evidence, or an AI practitioner seeking stronger statistical foundations, this book provides a structured path from fundamental concepts to modern applications.Understand the data. Test the hypothesis. Quantify uncertainty. Make better AI decisions.

When anxiety or panic makes you feel alone, this quiet book will sit beside you. These gentle reflections offer understanding, kindness and hope without asking you to be perfect.

Cybersecurity is no longer just an IT problem. Modern Information Security connects the principles, architecture, operations and strategy behind effective security programs. From identity and cloud security to incident response, governance and emerging threats, it offers practical guidance for building security that works in the real world.

一套普通人也能上手的 AI 研究方法论：用三天时间，把任何一件事查到心里有底。

一份所有验证都通过、原始授权却从未存在的永久代理权，把审计员顾迟和整座城市推向七十二小时倒计时。撤回一切并不自动等于正义。

I CAN'T WALK. I CAN BARELY MOVE MY HANDS. SO I BUILT MYSELF WINGS.

What happens when AI agents stop working alone and start working as a team?Artificial Intelligence is entering a new phase in which intelligent systems can do more than respond to individual instructions. Multiple specialized agents can collaborate, divide complex tasks, communicate with one another, use tools, evaluate results, and coordinate their actions toward a shared objective.Multi-Agent AI Systems: The Complete Handbook for Building Intelligent, Scalable, and Autonomous Agent Teams provides a practical roadmap for understanding this emerging paradigm.The book begins with the fundamentals of multi-agent systems and explains why collaboration between specialized agents can be valuable for complex workflows. Readers will learn about hierarchical, peer-to-peer, and hybrid architectures, along with roles such as manager, planner, worker, critic, and supervisor agents.It then moves into modern frameworks and technologies, including CrewAI, AutoGen, LangGraph, MetaGPT, LLMs, vector databases, and agent memory systems. Practical chapters explain how to design agent teams, decompose tasks, establish communication protocols, manage shared memory, coordinate workflows, integrate tools and APIs, and recover from failures.Readers will also explore advanced concepts such as dynamic replanning, parallel execution, swarm intelligence, agent debates, self-organizing systems, human-in-the-loop workflows, and multimodal agents.The book goes beyond experimentation and addresses the challenges of deploying multi-agent systems in real environments. Cloud deployment, Docker, Kubernetes, monitoring, logging, scaling, evaluation, benchmarking, testing, and cost optimization are included.Real-world applications demonstrate how agent teams can support software development, research, customer service, content creation, and business operations.Equally important, the book examines AI safety, privacy, security, transparency, governance, alignment, and responsible AI development.Whether you are a student discovering agentic AI, a developer building your first agent team, a researcher exploring collaborative intelligence, or a professional preparing for the next generation of AI applications, this book provides a foundation for moving from individual AI agents toward coordinated intelligent systems.Understand the architecture. Design the team. Build the agents. Coordinate the intelligence.

Master VB.NET through focused practice and systematic revision.Preparing for a VB.NET examination or technical interview? Looking for a comprehensive resource that combines theory with programming practice? Mastering VB.NET QUESTION BANK: 1000+ Conceptual Questions for Students and Professionals is designed to help students and aspiring software professionals strengthen their knowledge of Visual Basic .NET.The book provides a structured collection of questions covering VB.NET from fundamental programming concepts to advanced application-development topics.You will begin with the history, features, and structure of VB.NET before progressing through data types, variables, constants, operators, expressions, conditional statements, loops, procedures, functions, recursion, arrays, and collections.The book then moves into Object-Oriented Programming, covering classes, objects, inheritance, polymorphism, encapsulation, abstraction, interfaces, and constructors. Further chapters explore exception handling, debugging, file handling, Windows Forms, GUI programming, and database connectivity using ADO.NET.Advanced topics such as delegates, events, multithreading basics, LINQ to Objects, and XML are also included.Each chapter follows a consistent practice format containing 50 MCQs, 25 Short Answer Questions, 15 Mid-Length Answer Questions with Answers, and 20 Programming Questions with Answers. This makes the book suitable for both examination preparation and hands-on programming practice.Students pursuing BCA, MCA, B.Tech, M.Tech, Computer Science, Information Technology, and related programmes can use the book for university examinations, assignments, internal assessments, viva preparation, and practical tests.Educators can use the question bank to develop classroom quizzes, assignments, tests, and practical examinations. Software professionals and interview candidates can use it for focused revision and technical interview preparation.The programming exercises encourage readers to move beyond memorizing syntax and develop logical thinking and application-building skills.Study the concept. Attempt the question. Write the program. Check the answer. Improve your skills.

Start your programming journey with Visual Basic .NET.Have you always wanted to learn programming but found programming languages difficult or confusing? Visual Basic .NET for Beginners: A Step-by-Step Guide to Learning VB.NET is designed to provide a simple, structured, and practical introduction to VB.NET.This book takes you step by step through the fundamentals of programming and gradually introduces more advanced concepts. You will learn how to work with variables, data types, operators, conditional statements, loops, procedures, functions, arrays, and other essential programming features.The book also introduces the principles of event-driven programming and Object-Oriented Programming, helping you understand how modern applications are designed and developed.As you progress, you will explore practical application development concepts, user interfaces, database connectivity, error handling, debugging, and other important programming skills.The learning approach is focused on understanding and practice. Instead of simply presenting programming theory, the book encourages you to work with examples, experiment with code, identify errors, and develop solutions to programming problems.This makes the book useful for students, beginners, educators, and anyone who wants to build a foundation in VB.NET.Whether you are studying programming as part of an academic course, preparing for practical examinations, learning software development, or exploring the .NET ecosystem, this book can serve as a useful learning companion.You do not need to be an experienced programmer to begin. The concepts are introduced progressively so that you can build confidence as you move from basic programming statements toward complete application development.Learn the fundamentals. Practice the code. Understand the logic. Build your first VB.NET applications.