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 MANIPULATION HACKS: 101 MIND-BENDING FACTS: The Ultimate Collection of Psychological Insights, Covert Persuasion, and Brainwashing Secrets (Vol. 3) English | May 26, 2026 | ASIN: B0GX32VKKV | 105 pages | Epub | 334.67 KB Weaponize 101 Extreme Psychological Tactics to Decode Covert Persuasion, Outsmart Brainwashing, and Achieve Absolute Social Dominance.The ultimate level of influence is not about making people change their minds; it is about making them believe your ideas were theirs all along. Every single day, your perceptions are being systematically targeted. From cutting-edge marketing algorithms to highly sophisticated corporate compliance strategies and hidden conversational traps-there is a silent war being waged for control over your decision-making process.MANIPULATION HACKS: 101 MIND-BENDING FACTS is the crown jewel of your tactical psychological armory. Curated and sharp-focused by 101 Facts Factory, Volume 3 dives deep into the most advanced, counterintuitive behavioral mechanisms ever observed in social psychology. No academic padding, no filler-just 101 raw blueprints for human compliance.Every fact utilizes the signature high-speed framework: the Tactical Concept, the Subconscious Mechanism, and an immediate, battle-tested What It Is For implementation matrix. Flip to any page, master an elite psychological hack in 30 seconds, and use it to control the room, negotiate with absolute leverage, or build an impenetrable mental armor.Inside Volume 3 of this definitive series, you will discover:The "Oops, I'm So Clumsy" Trick: A brilliant micro-maneuver engineered to deliberately bypass critical defenses by exploiting evolutionary chemical triggers like oxytocin.The "Magical Number Seven" Compliance Framework: How to exploit Miller's Law to structure pricing, pitches, and proposals so the human brain processes them as uniquely optimal and undeniable.The Door-in-the-Face Rejection Leverage: How to systematically engineer an immediate "yes" by anchoring a reasonable request right behind an outrageously large, calculated rejection.Covert Persuasion & Brainwashing Countermeasures: The exact tactical breakdowns you need to recognize psychological manipulation, cognitive bias exploitation, and gaslighting instantly.High-Velocity Real-World Blueprints: Concrete action plans showing you exactly how to execute or neutralize these tactical levers in networking events, executive boards, high-stakes sales, and daily social circles.This is the definitive manual to human behavior. Whether you are an ambitious executive navigating toxic office politics, an entrepreneur looking to dominate your market, or a self-defense enthusiast protecting your mental boundaries, this volume completes your psychological armor.The rules of engagement have been laid out. It's time to seize absolute control of the board.Scroll up, click "Buy Now" or "Read Now" with Kindle Unlimited, and command absolute psychological leverage today!  MACHINE LEARNING MATHEMATICS Essential Linear Algebra, Calculus, Probability, Statistics, and Optimization for AI : 1,100+ Practice Problems with Fully Worked Solutions From Beginner to Intermediate English | June 15, 2026 | ASIN: B0H5C5V2VT | 444 pages | Epub | 3.01 MB Machine Learning Mathematics WorkbookMaster the mathematics that powers modern artificial intelligence and machine learning.Whether you're a student, aspiring data scientist, software engineer, AI enthusiast, or working professional, Machine Learning Mathematics Workbook provides the mathematical foundation needed to understand how machine learning algorithms work-not just how to use them.Unlike theory-heavy textbooks that overwhelm readers with abstract proofs, this workbook focuses on practical understanding through extensive guided practice. Every chapter begins with clear explanations, followed by worked examples, practice exercises, challenge problems, and complete step-by-step solutions.The content is carefully organized to take you from fundamental concepts to the mathematics behind neural networks and modern AI systems.What You'll LearnLinear Algebra for Machine LearningVectors and vector operationsMatrices and matrix multiplicationEigenvalues and eigenvectorsPrincipal Component Analysis (PCA)Dimensionality reduction techniquesCalculus for OptimizationFunctions used in machine learningDerivatives and differentiationPartial derivativesGradients and gradient descentOptimization fundamentalsProbability and StatisticsProbability theoryConditional probabilityBayes' TheoremRandom variables and distributionsDescriptive statisticsStatistical inference and samplingMachine Learning MathematicsLinear regression mathematicsLogistic regression mathematicsLoss functionsRegularization methodsBias-variance tradeoffNeural network fundamentalsBackpropagation mathematicsInside This Workbook1,100+ practice problemsFully worked solutionsBeginner-friendly explanationsProgressive difficulty levelsReal machine learning applicationsDiagnostic assessmentFour comprehensive examsFormula sheets and cheat sheetsPython examples for verificationWho This Book Is ForMachine learning studentsData science learnersComputer science majorsSoftware engineers entering AIGraduate studentsSelf-taught programmersAI practitioners seeking stronger mathematical foundationsWhy This Workbook Is DifferentMany machine learning resources teach algorithms without explaining the mathematics behind them. Others focus so heavily on theory that practical understanding gets lost.This workbook bridges that gap by combining mathematical rigor with hands-on practice. Every concept is reinforced through exercises and complete solutions, helping you build genuine problem-solving skills rather than passive familiarity.By the end of this workbook, you will understand the mathematical principles that drive machine learning models, optimization algorithms, statistical inference, and neural networks.Build the mathematical confidence needed to move from using machine learning tools to truly understanding how they work.  Lösungsbuch zum Buch Mathematik Grundlagen: Lerne Schritt für Schritt mit klaren und vollständigen Lösungen (Lizentiatsstudium Mathematik) Deutsch | August 27, 2025 | ASIN: B0FNW4WNM6 | 166 Seiten | PDF | 1.73 MB 📘 Bereit, eine solide Grundlage in den Grundlagen der Mathematik aufzubauen?Grundlagen der Mathematik ist der erste Band der Reihe Lizentiatsstudium Mathematik und richtet sich an Studierende, Dozenten und Fachleute, die die wesentlichen Grundlagen der Mathematik verstehen möchten. Mit einem klaren und progressiven Ansatz behandelt dieses Buch Themen von den reellen Zahlen bis hin zu Gleichungssystemen, Vektoren und Matrizen.🔍 Was findest du in diesem Buch?✅ Reelle Zahlen und grundlegende OperationenUmfassende Übersicht über algebraische Eigenschaften, Absolutwert, Potenzen, Wurzeln und die Verwendung wissenschaftlicher Notation.✅ Gleichungen, Ungleichungen und komplexe ZahlenTechniken zur Lösung linearer und quadratischer Gleichungen sowie Einführung in die Menge der komplexen Zahlen.✅ Vektoren und Analytische GeometrieDetaillierte Untersuchung von Vektoren in der Ebene, Abständen zwischen Punkten, Geraden und Kreisen.✅ Matrizen und GleichungssystemeZentrale Konzepte der Matrizenalgebra und Lösung von Systemen mit Methoden wie dem Gauß-Verfahren und Determinanten.✅ Gelöste und vorgeschlagene AufgabenJedes Kapitel enthält klare Beispiele und eine Vielzahl von Übungen, die das Lernen und das selbstständige Üben fördern.⭐ Hervorstechende Merkmale:✔ Zugängliche und dennoch strenge Erklärungen: Ideal für alle, die mit ihrem Mathematikstudium beginnen.✔ Kontextualisierte Anwendungen: Bezug zu Physik, Ingenieurwesen und angewandten Wissenschaften.✔ Didaktische Struktur: Entwickelt, um das Lernen Schritt für Schritt zu erleichtern.📖 Für wen ist dieses Buch gedacht?📌 Universitätsstudierende im ersten Semester, die ein klares und vollständiges Material suchen.📌 Lehrende, die einen strukturierten Text für Einführungskurse benötigen.📌 Autodidakten, die ihre mathematischen Grundkenntnisse vertiefen möchten.Mit einer ausgewogenen Kombination aus Theorie und Praxis ist Grundlagen der Mathematik die unverzichtbare Ressource für das unabhängige oder akademische Studium.  Lust auf fremde Küche: NENI - Die Rezept-Klassiker Deutsch | 21 Jun. 2023 | ISBN: 3990502506 | 176 Seiten | EPUB (True) | 28.41 MB Der NENI-Klassiker für die nächste Generation Was als kleines Lokal am Wiener Naschmarkt begann, ist heute als international erfolgreiche Marke nicht mehr wegzudenken: NENI steht von Wien bis Paris, von Berlin bis Mallorca für genussvolle, moderne orientalische Küche, die meisterhaft traditionelle Rezepte mit innovativen Ideen kombiniert. Dass Klassiker wie Hummus, Falafel & Co. vor einigen Jahren noch als fremde Küche gelten konnten, ist dank Haya Molcho längst Geschichte: NENI verheißt unvergessliche Geschmackserlebnisse, Lebensfreude pur und macht neugierig auf das Entdecken von anderen Ländern, Menschen und deren Kochkultur - Lust auf fremde Küche ist dabei Programm. Die kreativen und einfachen Rezepte aus Haya Molchos Kochbuchklassiker begeistern nicht nur Restaurantbesucherinnen und -besucher von Generation zu Generation, sondern auch ihre eigene Familie. Kombiniert mit persönlichen Geschichten ist das Buch eine Hommage an gutes Essen, Hayas Leidenschaft fürs Kochen und vor allem ihre Familie, die seit Kurzem ein neues Mitglied zählt: Hayas erstes Enkelkind, dem dieses Buch gewidmet ist. HINWEIS: Falls Sie sich wundern, warum das Buch scheinbar verkehrt herum gebunden ist - das hat schon seine Richtigkeit. Es ist entsprechend dem Hebräischen VON RECHTS NACH LINKS zu lesen. Die OFFENE FADENHEFTUNG dient der praktischen Handhabung beim Kochen.  Luftfahrt Vorschriften Deutsch | 22 Feb. 2026 | ASIN: B0GPW1DCTN | 162 Seiten | EPUB (True) | 20.44 MB  Loop Engineering: Scaling and Governing Agentic AI English | June 15, 2026 | ASIN: B0H4X5CZM4 | 283 pages | Epub | 4.24 MB The hard part of agentic AI is not the demo. It is the loop that has to survive contact with real users.Anyone can wire up an agent that works in a notebook. The leverage in working with language models has moved again - from prompt engineering (what to say) and context engineering (what to provide) to loop engineering: designing the whole system that plans, acts, observes, and revises on its own. This book is a blueprint for the distance most teams underestimate - the distance between a fragile "laptop loop" running under a personal credential and a governed, secure, self-improving system you can trust with a real budget and real consequences.Written for engineers who want the mechanism, the systems, and the trade-offs rather than the hype, it builds every idea from first principles and spends as much time on what goes wrong as on what goes right.What you will learnThe anatomy of an agentic loop - the ReAct pattern, why dynamic loops outperform fixed prompt chains, and how to turn "make it better" into a verifiable stopping condition.The six primitives of durable systems - automations, worktrees, skills, connectors (MCP), the maker/checker split, and external memory.Choosing an orchestration framework - LangGraph, AutoGen, and CrewAI, matched to the shape of your workflow with a simple Diagram Test.From laptop loops to LLMOps - why operating language systems differs from MLOps, and how an AI gateway centralizes fallbacks, budgets, and observability.Sovereign agentic loops - why model output must never be an executable command, the obfuscation membrane, deterministic policy evaluation with Open Policy Agent, and a cryptographic evidence chain for replayable audits.Human-in-the-loop controls - the four rungs of autonomy, how to fight automation bias, and interface patterns that show a human the consequences before they approve.Automated evaluation - LLM-as-a-Judge, the biases that will fool you, and scoring methods that make automated judgment trustworthy.The slow risks - comprehension debt and model collapse, why they stay invisible until they are expensive, and how to design against them.Balanced, runnable code sits alongside the prose, with diagrams for the architectures and a full set of appendices: the formal mathematics, an orchestration-framework matrix, a catalog of human-in-the-loop interface patterns, and a glossary of the vocabulary this discipline has accumulated.Who this is for: engineers and technical leaders building agentic software that has to run unattended, at scale, under scrutiny - and anyone who would rather understand why a system works than be told that it does.Take the loop apart, wrap it in governance and honest feedback, and keep a person meaningfully in charge. That is the work this book teaches.  Lock Picking for Beginners: A Complete Step-by-Step Guide to Lock Picking Tools, Practice Locks, Tension Control, Pin Tumblers, Padlocks, and Ethical Entry Skills English | May 28, 2026 | ASIN: B0H3676QZY | 81 pages | Epub | 541.22 KB What if a simple lock could teach patience, focus, and mechanical understanding?Lock Picking for Beginners is a clear, responsible, beginner-friendly guide to the lawful craft of lock picking. Written for readers who want to understand locks-not misuse them-this book explains the tools, techniques, and mindset behind ethical entry skills in a practical, step-by-step way.Inside, readers will learn how pin tumbler locks work, what tension control really means, how practice locks build skill, and why patience matters more than force. From basic tools and safety rules to padlocks, keyways, feedback, and troubleshooting, this guide helps beginners build confidence without confusion.This book is ideal for hobbyists, preparedness-minded readers, locksmithing students, DIY learners, and anyone curious about mechanical security.✅ Learn the basics of lock picking responsibly✅ Understand pin tumblers, tension, and feedback✅ Practice with training locks and owned property only✅ Build skill through patience, control, and repetition✅ Avoid beginner mistakes that damage locks or toolsLock picking is not about shortcuts. It is about understanding.  Lock In: How to Think Deeply in a Shallow World English | May 31, 2026 | ASIN: B0H3GD6NC3 | 128 pages | Epub | 831.60 KB In a world designed to keep your mind scattered, can you still think deeply?Every day, your attention is stolen by notifications, endless feeds, and shallow content. Your brain is exhausted before it even begins meaningful work. Focus has become a luxury most people can no longer afford.Lock In is your practical guide to reclaiming your mind in the age of distraction.Written by Diep Pham, author of Unlock the Stupid Inside, this book delivers a complete system to:Build unbreakable focus even when your environment is chaoticTrain your brain to think deeply in a world that rewards shallow thinkingDesign a "Focus Fortress" that protects your attentionMaster the psychology and habits of elite thinkers and high performersTurn deep work into your greatest competitive advantageWhether you're a student, entrepreneur, writer, or professional who wants to stop feeling mentally drained and start producing your best work, Lock In gives you the exact framework to think clearly, work powerfully, and create something meaningful in a distracted world.This is not just another productivity book.This is mental training for the modern world.If you're tired of feeling scattered and ready to finally Lock In - scroll up and click "Buy Now".Your deepest thinking self is waiting.  LlamaIndex Workflows: Data‑Connected Agents with Repeatable Retrieval Pipelines English | 20 May 2026 | ASIN: B0H2H3YJ7J | 333 pages | EPUB (True) | 7.50 MB "LlamaIndex Workflows: Data‑Connected Agents with Repeatable Retrieval Pipelines"Modern LLM systems fail not only because models hallucinate, but because orchestration is hidden, retrieval is underspecified, and agent behavior is difficult to inspect or reproduce. This book is written for experienced AI engineers, platform architects, and advanced Python practitioners who need explicit control over data-connected applications. It shows how to use LlamaIndex Workflows as a disciplined runtime for building retrieval pipelines and agents whose behavior can be understood, tested, and operated with confidence.Across the book, readers learn how workflows model execution through typed events, steps, context, and state; how repeatable retrieval systems are engineered from ingestion and indexing through reranking and synthesis; and how agent loops can be decomposed into inspectable planning, retrieval, tool-use, and termination stages. The coverage extends beyond implementation to durability, observability, testing, regression control, and production reliability, enabling readers to design systems that remain stable as data, prompts, packages, and operational conditions evolve.Rather than presenting convenience abstractions as magic, the book treats them as design choices with measurable trade-offs. Readers should already be comfortable with Python, LLM application architecture, and retrieval-augmented generation concepts. In return, they gain a rigorous, architecture-first guide to building transparent, replayable, and maintainable LlamaIndex systems for serious production us  Llama 4 Explained: In-depth explanation of Llama 4 code architecture English | May 12, 2026 | ASIN: B0H1J3M18D | 88 pages | PDF | 3.92 MB Learn how a modern open-weight large language model works, from first principles to advanced Mixture-of-Experts internals.Llama 4 From First Principles To MoE Internals is a practical, code-focused guide for readers who want to understand the architecture behind Llama 4-style language models. The book starts with the foundations of next-token prediction, transformer blocks, tensor shapes, and PyTorch operations, then gradually builds toward attention, KV caching, RoPE, RMSNorm, SwiGLU, tensor parallelism, and sparse expert routing.Rather than treating LLMs as black boxes, this ebook walks through the actual mechanisms that make them work. Important code snippets are presented clearly and explained step by step, helping readers connect mathematical ideas to real implementation patterns.Inside, you will learn:How transformer blocks process tokens through attention and feed-forward layersHow RoPE, RMSNorm, SiLU, SwiGLU, and KV cache fit into an LLM inference pipelineHow scaled dot-product attention works in practiceHow tensor shapes move through query, key, value, and feed-forward computationshow Mixture-of-Experts routing selects experts and reduces active computationHow Llama 4-style MoE layers, expert batches, and load hooks are implementedHow PyTorch code maps directly to LLM architecture concepts This book is designed for students, engineers, and AI practitioners who want a deeper technical understanding of LLM internals without jumping straight into dense research papers or unexplained source code.If you want to move beyond high-level explanations and understand how modern LLM components actually work together, this ebook provides a structured path from beginner-friendly concepts to advanced Llama 4 internals.This is an independent educational work and is not affiliated with or endorsed by Meta. |
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