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Prompt Intelligence
English | October 6, 2026 | ASIN: B0HM3GRYM3 | 304 pages | Epub | 910.81 KB
PROMPT INTELLIGENCEAn Advanced Manual of Systematic Engineering with ChatGPT to Automate Your BusinessStop just "trying things" with ChatGPT and start working with a system.Most people use ChatGPT like a search engine that talks: they type a sentence, get an acceptable answer, and start from scratch again the next day. Prompt Intelligence offers a different way of working—one where every instruction becomes a professional asset: designed, verified, and reusable, capable of saving you and your business real hours. This advanced manual, updated for 2026, takes you from setting up your environment all the way to orchestrating AI agents, with a clear method, practical examples, and templates you can start adapting today.What You'll LearnHow a language model works under the hood, what it can and can't do, and how to avoid its errors and hallucinations.How to build professional prompts using a proprietary framework, reasoning techniques, and advanced dialogue methodologies.How to audit and improve your prompts through reverse engineering.How to work with documents, data, images, and voice: text extraction, data analysis, and in-depth research using web search.How to create AI agents and multi-agent workflows to automate repetitive tasks.How to protect privacy and manage the risks of using AI in your organization.How to turn your prompts into business assets: libraries, standards, and teamwork.How to apply all of this to office work, technical and creative content, learning, and industry-specific cases (legal and advisory services, health and wellness, education, and personal finance), always with clear boundaries.Includes the Master Prompt Library: 30 ready-to-copy templates organized by work area—fundamentals and verification, office and productivity, business and data, communication, creativity, agents and governance, and learning.A Manual That Never Goes Out of Date: AI moves fast. That's why the final chapter, "The Living Manual," gives you protocols for checking with the tool itself which content still holds up, so you can keep what works for you even after the book itself has fallen behind.Who This Book Is For: Freelancers, entrepreneurs, executives, office teams, and professionals who already use ChatGPT and know they could be getting a lot more out of it.An independent work, not affiliated with, sponsored by, or endorsed by OpenAI.

Prompt Engineering: Image & Video: The Only Guide You'll Ever Need for AI Image and Video Generation, From First Prompt to Professional Output.
English | 22 Sept. 2026 | ASIN: B0HKQ2X2Z8 | 380 pages | Epub | 77.41 MB

Production MLOps for Quant Trading: Building and Monitoring Infrastructure on Kubernetes
English | September 14, 2026 | ASIN: B0HJSLGXK1 | 565 pages | Epub | 2.93 MB
Reactive PublishingBuild, deploy, and scale institutional-grade machine learning pipelines designed specifically for high-frequency and quantitative trading environments.In quantitative finance, model latency, feature staleness, and unmonitored drift directly translate to financial loss. Production MLOps for Quant Trading delivers a practical, hands-on blueprint for building resilient, continuous-delivery ML systems on Kubernetes-tailored to the zero-tolerance demands of live market execution.This book skips theoretical high-level overviews to focus on the concrete engineering challenges quant developers, MLOps engineers, and financial data scientists face daily:Automated CI/CD Pipelines: Design and execute robust testing, validation, and deployment automation for live algorithmic models.Low-Latency Feature Stores: Implement real-time and batch feature management to eliminate training-serving skew in dynamic markets.Model Drift & Anomaly Detection: Detect concept drift, covariate shift, and signal decay before bad trades execute.Kubernetes Infrastructure: Orchestrate distributed training, auto-scaling, and self-healing workloads on enterprise cloud environments.Packed with production-ready architectures, actionable code patterns, and real-world trade-offs, this guide provides the exact technical roadmap needed to bridge the gap between backtested alpha and live trading execution.

Production Agentic AI Engineering: Building Autonomous LLM Agents for Real-World Deployment
English | September 25, 2026 | ASIN: B0HL1W9DL9 | Pages not found | PDF | 17.82 MB
Building an AI agent that works in a demo is one thing. Building one that works reliably in production—at scale, inside a real organization, and under real governance requirements—is a different engineering discipline entirely.Production Agentic AI Engineering is a practical guide to designing, building, deploying, and operating autonomous LLM agents for real-world environments. It takes a production-first approach, connecting agent architecture with memory, tools, evaluation, observability, governance, and cost control.WHAT YOU WILL LEARNDesign production-ready agent architectures and understand the four-layer agentic stackBuild prompt architectures that can be versioned, tested, evaluated, and deployed systematicallyDesign working, episodic, and semantic memory systems, including RAGBuild multi-agent workflows for delegation, shared state, coordination, and conflict resolutionEvaluate and test non-deterministic, multi-step agent behaviorUse observability, tracing, and systematic debugging to diagnose production failuresApply governance, guardrails, audit trails, and human oversight to agentic systemsManage token budgets, model routing, caching, and other approaches to production cost controlWHAT MAKES THIS BOOK DIFFERENTFour production-focused case studies covering customer support, data analysis, code review, and research synthesisDetailed examination of design decisions, failure modes, and engineering solutionsPractical production principles rather than demo-focused examplesArchitectural concepts designed to remain useful across different model providers and frameworksPython examples using the Anthropic SDKWHO THIS BOOK IS FORSoftware engineers designing and building production agent systemsTechnical architects responsible for AI deployment infrastructureEngineering managers who need a practical understanding of production agentic AIIf you are building agentic AI systems that need to work in production—not just in a notebook—this book provides a practical framework for designing, deploying, operating, and improving them.

Predictive Analytics with Python: Build Production-Ready Predictive Models with Polars, Pandera, Scikit-Learn, XGBoost, MLflow, FastAPI, Docker, and Python
English | September 18, 2026 | ISBN: 8169646596 | 491 pages | EPUB (True) | 99.79 MB
Build Models That Survive Beyond the Notebook.Key Features● Get a free one-month digital subscription towww.avaskillshelf.com.●Production-first data pipeline engineering using Polars for high-performance ETL and Pandera for data contracts.● Full MLOps lifecycle coverage with CRISP-DM, Scikit-Learn, XGBoost, MLflow experiment tracking, and hyperparameter tuning.● Enterprise-grade capstone project building an Automated Valuation Model deployed with Docker and FastAPI.Book DescriptionData Science Finds the Signal. Engineering Turns It into Business Value.Moving a model from a Jupyter Notebook to a production system requires engineering discipline, not just data science skills. Predictive Analytics with Python is the definitive guide for the engineering-first era of data science, helping you transition from fragile notebook workflows to resilient, production-ready predictive systems built for real-world infrastructure.You begin by replacing slow legacy workflows with a modern technical stack, high-performance ETL with Polars, data contract enforcement with Pandera, and resilient Scikit-Learn and XGBoost pipelines with rigorous feature engineering, cross-validation, and experiment tracking using MLflow. The book then advances into time-series forecasting with Nixtla before covering model serialisation, REST API deployment with FastAPI, Docker containerisation, and production monitoring as well as governance.The book culminates in an end-to-end capstone project building an enterprise-grade Automated Real Estate Valuation Model. By the end, you will engineer predictive systems that prioritize stability, auditability, and transformative business value.What you will learn● Transition fragile notebook workflows into robust production-grade software engineering practices.● Execute high-performance ETL and data processing using the Polars library at scale.● Enforce rigorous data contracts using Pandera to validate pipeline inputs automatically.● Build resilient predictive pipelines using Scikit-Learn and XGBoost with production patterns.● Automate hyperparameter tuning and track model experiments using MLflow effectively.● Deploy production predictive models as REST APIs using Docker and FastAPI.Table of Contents1. From Notebooks to Systems2. The Modern Python Environment3. High-Performance ETL with Polars4. Defensive Data Programming with Pandera5. Feature Engineering as Software6. Handling Real-World Messiness7. The Baseline: Linear Pipelines8. Productionizing Gradient Boosting (XGBoost)9. The Tuning Lifecycle and Experiment Tracking10. Model Evaluation and Interpretation11. Engineering Time-Series Features12. Modern Forecasting with Nixtla13. The Deployment Gap: Serialization and Packaging14. Serving Predictions with APIs15. Monitoring and Model Governance16. Capstone: Building the Enterprise AVM Index

Practical Python in the AI Era: Build Real Programs with Automation, APIs, Testing, and AI-Assisted Coding (CodeEssentials Python Series Book 2)
English | October 9, 2026 | ASIN: B0HMJLGLZ3 | 205 pages | Epub | 518.90 KB
Tested with Python 3.15. Already know the Python basics and ready to build something useful?Practical Python in the AI Era turns basic Python knowledge into real, working programs. It is modern Python for the way people code today, when AI can write a script in seconds but someone still has to understand it, test it, and make it do the right thing.After a fast refresher and a self-check, you will learn to:Automate real work: organize folders, rename and move files safely, and generate reportsWork with dаta: read, clean, and write CSV and JSONConnect to web APIs: fetch data safely, with timeouts and proper error handlingBuild command-line tools with argparse, and structure projects with modules, packages, and virtual environmentsTest with pytest and debug real programs instead of guessingUse AI-assisted development well: get explanations, hints, and test cases from AI, and catch the invented methods and missing error handling that AI-generated code often hidesFive useful projects, built step by step in the book: a smart file organizer, a text and log analyzer, an expense tracker that imports bank CSV files, a contact manager, and a command-line task tracker with a full test suite.What matters in Python 3.15 (friendlier error hints, UTF-8 by default, frozendict, and more) is covered in one focused chapter. Every example was tested with Python 3.15 and runs on Python 3.12 and newer.Free bonus included: readers get a free reader bonus with extra exercises, project extensions, and resources, plus downloadable companion files with the code, sample data, and answers for every chapter and project. Scan the QR code inside the book to get them.Practical Python in the AI Era is Book 2 of the CodeEssentials Python Series and works on its own. New to programming? Python for Beginners (Book 1) is the gentler start. Already know the basics, from anywhere? You are ready for this book.

Practical Claude Code: How to Build Applications, Work with Codebases, Debug Problems, Automate Tasks, and Ship Real Software with AI
English | October 9, 2026 | ASIN: B0HMJ2J8CC | 202 pages | PDF | 5.06 MB
Stop Using AI to Just Write Code,Start Using It to Build Better SoftwareClaude Code can do far more than generate snippets. The real advantage comes from knowing how to use it across the full development workflow—planning features, understanding unfamiliar codebases, debugging failures, testing changes, automating repetitive tasks, and preparing software that is actually ready to ship.Practical Claude Code is a hands-on guide to using Claude Code as a serious software-development tool rather than a shortcut for producing code you do not fully understand.Inside, you will learn how to:• turn ideas and requirements into structured development plans;• work confidently with existing and unfamiliar codebases;• give Claude Code clearer, more effective development instructions;• debug problems using evidence instead of guesswork;• write, review, and verify tests;• refactor code without breaking existing behavior;• use Git to keep AI-assisted changes controlled and recoverable;• automate useful development workflows with skills, hooks, scripts, MCP, and subagents;• review AI-generated changes before accepting them;• prepare applications for release and move projects toward production.Every meaningful code snippet and command is accompanied by a brief explanation of what it does, why it is being used, and what you should expect from it—so you are not simply copying instructions without understanding them.What makes this book different is its focus on real development discipline.It does not teach you to hand over your project and hope the AI gets everything right. Instead, it shows you how to combine Claude Code's speed and reasoning capabilities with the software-engineering practices that keep projects understandable, testable, maintainable, and safe to change.The book follows a practical workflow you can reuse across projects:Explore → Plan → Build → Test → Review → Improve → ShipWhether you are starting a new application, working inside an existing repository, chasing down a difficult bug, or trying to reduce repetitive development work, Practical Claude Code gives you a clear process for getting more useful results from AI without giving up control of your code.If you want to move beyond AI-generated snippets and start using Claude Code to build, debug, automate, and ship real software, this book will show you how.

Plumbing Vent Systems Field Handbook: A Practical Guide for Trap Arms, Fixture Drainage, Wet and Circuit Venting, AAV Selection, IPC/UPC Review, Testing, Inspection, and Diagnosis
English | October 9, 2026 | ASIN: B0HMFCHWG6 | 538 pages | Epub | 16.68 MB
Plumbing Vent Systems Field Handbook is a practical reference for understanding how drain, waste, and vent systems actually function, why venting problems occur, and how properly designed air paths help protect fixture trap seals. Instead of treating venting as a collection of disconnected rules, the book explains the relationship between wastewater movement, air pressure, trap protection, pipe layout, and system performance. Plumbing Venting Handbook - Rev.Readers are guided from fundamental DWV principles into real installation, sizing, inspection, testing, and troubleshooting situations. The handbook also emphasizes an important field reality: a system can appear to drain normally and still have poor trap protection, incorrect vent geometry, or pressure problems that become noticeable only when several fixtures operate together. Plumbing Venting Handbook - Rev.Inside, you will learn how to:Understand DWV airflow, positive and negative pressure, siphonage, backpressure, and trap-seal protectionIdentify and measure traps, trap arms, vent connections, developed lengths, slopes, and drainage loadsPlan and evaluate individual vents, common vents, wet venting, circuit venting, waste-stack venting, and multi-fixture systemsWork with pipe sizing, fittings, materials, supports, offsets, penetrations, and installation geometryUnderstand the proper role and limitations of air admittance valves (AAVs)Compare IPC and UPC approaches while recognizing the importance of adopted editions, amendments, AHJ requirements, and product approvalsInspect roof terminals, flashing, vent headers, stack arrangements, and concealed pipingUse water, permitted air, vacuum, smoke, and final DWV testing methods appropriatelyDiagnose gurgling, bubbling, sewer-gas complaints, trap-seal loss, blocked or restricted vents, drainage restrictions, poor vent geometry, and pressure-related problemsApply systematic field procedures to observe, verify, isolate, correct, and retest plumbing problemsThe book gives special attention to advanced venting arrangements. Wet venting is presented as a defined hydraulic system rather than simply an oversized drain, while circuit and waste-stack venting are explained through fixture arrangement, drainage loading, air movement, vent location, and inspection requirements. Plumbing Venting Handbook - Rev.Code requirements are also approached from a practical standpoint. Because model codes, adopted editions, state amendments, local amendments, and AHJ requirements can differ, the handbook shows readers how to determine which rules actually govern a project instead of assuming that one national provision applies everywhere. Plumbing Venting Handbook - Rev.From initial layout and rough-in to testing, inspection, roof termination, troubleshooting, repairs, and final verification, Plumbing Vent Systems Field Handbook is designed to help readers see the entire venting system as one connected pressure-management network.Trace the drainage path. Understand the air path. Protect the trap. Verify the system.

Playing the Modes for Six and Seven-String Guitar: How to Build Modal Chords - 21 Modes of the Major, Melodic Minor and Harmonic Minor Scales, with 7-String Guitar Tabs
English | October 12, 2026 | ASIN: B0HMS81GQN | 147 pages | Epub | 13.00 MB
A mode is not a new scale to memorise. It is a parent scale with a different note treated as home - and it only exists while a chord holds that home note in place. This book teaches the modes that way: one mode at a time, through its characteristic note and the chords it produces.Each of the 21 chapters follows the same structure:The mode compared with the plain major or minor it resembles, so you hear the one note that changesThe mode harmonised on all seven degrees, with a chord diagram for every degreeA vamp that fixes the home note, built from the mode's own chordsThe scale in a fretboard box you already know, an original lick and a seven-string extensionPart 1: the seven modes of the major scale, from Ionian to Locrian.Part 2: the modes of the melodic minor, including Lydian dominant and the altered scale.Part 3: the modes of the harmonic minor, including Phrygian dominant.All tabs are written for seven-string guitar and can be read on a six-string: outside the seven-string sections, no note falls on the low B. No audio needed - every chapter tells you which chords to loop.A companion to From Reproducing to Creating, for intermediate players who know their chord tones and want to use modes over real chords.

Peak Human: What We Can Learn From History's Greatest Civilizations
English | May 29, 2025 | ASIN: B0F284VKNN | 583 Pages | EPUB (True) | 1.86 MB
All golden ages are marked by periods of spectacular cultural flourishing, scientific exploration, technological achievement and economic growth; yet no two are the same. Their beliefs, societies and place in the wider world all vary. Despite this, all previous golden ages have ended, whether it be because of external pressures or internal fracturing; too much hubris or too little wariness.Looking at seven of humanity's greatest civilisations - ancient Athens, the Roman Republic, Abbasid Baghdad, Song C hina, Renaissance Italy, the Dutch Republic and the Anglosphere - historian and commentator Johan Norberg seeks to distil their strengths and shortcomings in answering the question: how do we ensure that our current golden age doesn't end?As insightful as it is riveting, Peak Human is at once a paean to our incredible progress and a warning that we cannot afford to be complacent.