Computer Science

Laptop powers on, but the screen stays black? Learn how to troubleshoot no-display problems step by step. Discover practical methods for checking RAM, BIOS, LCD panels, backlights, display cables, GPU, and motherboard faults. A hands-on repair guide for beginners, hardware students, and technicians.

A production crisis. Three developers. Fifty cinematic comic lessons. Master Java threads, race conditions, synchronization, and deadlocks through an unforgettable manga-style adventure.

AI is changing the way we work, but its capabilities have limits that matter. Understanding What AI Cannot Do explores where AI falls short, which human skills remain valuable and how to build a career that can withstand technological change. Grounded in research and real-world examples, this book offers a clear-eyed guide to navigating an uncertain future.

Vague prompts produce vague results. This book shows developers how to write clear, testable prompts for real coding tasks—explanations, functions, debugging, tests, and more—using a simple, repeatable method: state the goal, give the right context, set constraints, define the output, and verify the result.Written for beginners and working developers who want better AI-assisted work without treating model output as automatically correct.

Life and AI are made of different stuff, yet they face many of the same problems. This book sets their solutions side by side, from the first cells to today's language models, to understand both.

为什么参数不大的模型，把信息放对地方就能反超更大的模型？本书以"压缩"为主线，把大模型的表示、泛化、推理、RAG 与智能体统一成一道信息管理题：什么该压、什么不能丢、什么该外置、放在哪里、何时取回。18 章、190 张原创图解，从熵一路讲到世界模型。

What really happens inside your computer?A click seems simple.A program opens.A file loads.A webpage appears.But underneath that simple experience, billions of electronic components and thousands of layers of software are working together.Inside the Machine takes you beneath the interface—from bits and logic gates to CPUs, memory, storage, operating systems, and applications.Discover how information becomes computation, how processors execute instructions, how memory and caches keep data moving, how operating systems manage the machine, and how a computer goes from power-on to a running application.Stop seeing the computer as a black box. Start seeing the machine.

AI can analyze the data. But who decides what the data means—and what to do next?Modern organizations have more information than ever, yet making good decisions remains difficult.AI-Powered Smart Decision Making shows how to combine AI, data, analytics, and human judgment to turn information into insight and insight into action.Discover a practical framework for making better decisions across strategy, marketing, sales, operations, finance, risk, and beyond.AI is not the decision. AI improves the decision process. Table of ContentsIntroduction—The New Era of AI-Powered Decision MakingChapter 1 — The Foundations of Better Business DecisionsChapter 2 — From Intuition to Data-Driven Decision MakingChapter 3 — Understanding Data for Better DecisionsChapter 4 — Business Analytics: Turning Data into InsightChapter 5 — How AI Changes Business Decision MakingChapter 6 — Building an AI-Powered Decision FrameworkChapter 7 — Asking the Right Questions: AI, Data & Decision ProblemsChapter 8 — Predictive Decision MakingChapter 9 — Prescriptive Analytics and Decision OptimizationChapter 10 — AI for Strategic Business DecisionsChapter 11 — AI for Marketing and Customer DecisionsChapter 12 — AI for Sales, Operations and Supply ChainChapter 13 — AI for Financial and Risk DecisionsChapter 14 — Human + AI: The New Decision-Making PartnershipChapter 15 — Bias, Uncertainty and the Limits of AI DecisionsChapter 16 — Trustworthy, Responsible and Explainable AI DecisionsChapter 17 — Measuring Decision Quality and Business ImpactChapter 18 — Building an AI-Powered Decision CultureChapter 19 — Designing an AI-Powered Decision SystemChapter 20 — The Future of Smart Decision MakingConclusion — From Data to Better DecisionsDisclaimer

Master Operations Research Through Concepts, Techniques, and Practical Problem-SolvingLearn Linear Programming, Simplex Methods, Transportation, Assignment, TSP, Network Analysis, CPM, PERT, Queuing Theory, Game Theory, and Sequencing through structured explanations, numerical examples, and step-by-step problem-solving techniques.

Start Your Computer Science Journey with Strong FundamentalsA beginner-friendly guide covering computer fundamentals, number systems, algorithms, programming, problem-solving, OOP, data structures, and file handling—with clear explanations, practical examples, exercises, and a step-by-step learning approach.

AI is no longer just a technology experiment.It is becoming part of how businesses communicate, process information, serve customers, manage workflows, analyze data, and make decisions.But where should AI actually be used?AI-Driven Operations provides a practical roadmap for answering that question.Discover how to:Find the right processes to automateTurn manual workflows into intelligent workflowsUse AI agents responsiblyConnect AI with business systemsReduce operational costsMeasure real business valueProtect data and maintain human oversightScale successful AI initiativesThe future of business is not about using the most AI.It is about using AI intelligently.

Stop fighting the noise. Learn how to read ambient data, insulate against invisible interference, and control your environment without lifting a finger—using Enterprise Architecture principles for your mental OS.

A Systems Architect's First-Principles field guide to decoding physical telemetry, reducing noise, and mastering silent communication with matter, hardware, and complex physical systems.

AI can generate an answer. But can it safely take action?AI agents are changing software by giving intelligent systems the ability to plan, use tools, interact with external systems, and execute multi-step workflows.Moving from an impressive prototype to a dependable production system, however, requires much more than a powerful model.AI Agents & Agentic Workflows in Production explores the engineering principles behind production-grade agentic systems—from architecture and tool use to memory, planning, orchestration, evaluation, security, reliability, observability, scalability, governance, and continuous operation.Learn how to build agents that don't just act—but act reliably, safely, measurably, and under control.

Security is no longer something you add after a system is built. It must be designed from the beginning.Security by Design explores how modern digital systems can be built to reduce risk, limit unauthorized access, protect sensitive data, detect threats, contain failures, and recover from attacks.From secure architecture and cybersecurity foundations to privacy, cloud security, DevSecOps, AI security, and digital resilience, this book provides a practical foundation for building systems that remain secure in an increasingly connected and AI-powered world.