Allgemein
Beginning Ethereum Smart Contracts Programming
Use this book to write an Ethereum blockchain smart contract, test it, deploy it, and create a web application to interact with your smart contract. This new edition has been expanded and updated to cover web3.js APIs, additional Consensus Protocols, non-Fungible Tokens (NFTs), developing NFT tokens using ERC-721, and more!BEGINNING ETHEREUM SMART CONTRACTS PROGRAMMING, SECOND EDITION is your fastest and most efficient means of getting started if you are unsure where to begin and how to connect to the Ethereum blockchain. The book begins with a foundational discussion of blockchain and the motivation behind it. From there, you will get up close and personal with the Ethereum blockchain, learning how to use an Ethereum client (geth) to create a private Ethereum blockchain to perform transactions such as sending Ethers to another account on another node.You will learn about smart contracts without having to wade through tons of documentation. Author Lee’s “learn-by-doing” approach will allow you to be productive and feel confident in your ability in no time. The last part of this book covers tokens, a topic that has taken the cryptocurrency market by storm.Sample code in Python, Solidity, and JavaScript is provided in the book and online.WHAT YOU'LL LEARN* Understand the basic premise of blockchain and “record keeping” in a peer-to-peer network* Experience blockchain in action by creating your own blockchain using Python* Know the foundation of smart contracts programming and how to deploy and test smart contracts* Work on a case study to illustrate the use of blockchain* Be familiar with tokens, and how to create and launch your own ICO digital token* Write smart contracts that transact using tokensWHO THIS BOOK IS FORThose who want to get started quickly with Ethereum smart contracts programming. Basic programming knowledge and an understanding of Python or JavaScript is recommended.WEI-MENG LEE is the founder of Developer Learning Solutions, a technology company specializing in hands-on training of blockchain and other emerging technologies. He has many years of training expertise and his courses emphasize a learn-by-doing approach. He is a master at making learning a new programming language or technology less intimidating and fun. He can be found speaking at conferences worldwide such as NDC and he regularly contributes to online and print publications such as DevX.com, MobiForge.com, and CoDe Magazine. He is active on social media on his blog learn2develop.net, on Facebook at DeveloperLearningSolutions, on Twitter @weimenglee, and on LinkedIn at leeweimeng.---NEW Chapter----CHAPTER 1 - TECHNOLOGIES BEHIND BLOCKCHAINBASIC CRYPTOGRAPHYTYPES OF CRYPTOGRAPHIC ALGORITHMSSYMMETRICASYMMETRICHASHINGDIGITAL SIGNATURESUMMARYChapter 2 - Understanding Blockchain---NEW SECTION---CONSENSUS PROTOCOLSPROOF OF STAKE (POS)PROOF OF ELAPSED TIMEPROOF OF SPACE...-----------------Chapter 3 - Implementing Your Own Blockchain using PythonChapter 4 - Connecting to the Ethereum Blockchain using GethChapter 5 - Creating Your Own Private Ethereum Test NetworksChapter 6 - Using the Crypto Wallet - MetaMaskChapter 7 - Getting Started with Solidity Smart ContractsChapter 8 - Testing Smart Contracts using GanacheChapter 9 - Building Decentralized Apps using the web3.js APIsChapter 10 - Handling Smart Contract EventsChapter 11 - Project - Online LotteryChapter 12 - Creating Tokens using ERC-20---REVISED USING OPENZEPPLIN’S CONTRACT------NEW CHAPTERS----CHAPTER 13 - CREATING NON-FUNGIBLE TOKENS USING ERC-721WHAT IS A NFT?STORING DIGITAL ASSETS USING IPFSWHAT IS IPFSUPLOADING A FILE TO IPFSACCESSING A FILE FROM IPFSNFT AND IPFSCREATING THE NFT TOKEN CONTRACTDEPLOYING THE CONTRACTMINTING THE NFT TOKEN CONTRACTGETTING THE OWNER OF THE NFTGETTING THE NAME AND SYMBOL OF NFTFINDING THE BALANCE OF NFT FOR AN ADDRESSGETTING THE OWNER OF THE NFTGETTING THE TOKENURITRANSFERRING A NFTTRANSFERRING OWNERSHIP OF THE NFT CONTRACTCHAPTER 14 – INTRODUCTION TO DEFIWHAT IS DECENTRALIZED FINANCESTABLECOINSTYPES OF STABLECOINSUSDCDAISERVICES IN DEFICOMPONENTS IN DEFIAPPLICATIONS OF DEFI------------------
Microsoft Azure AI Fundamentals Certification Companion
Prepare for the Azure AI Fundamentals certification examination. This book covers the basics of implementing various Azure AI services in your business. The book not only helps you get ready for the AI-900 exam, but also helps you get started in the artificial intelligence (AI) world.The book starts with a short overview of the AI-900 exam and takes you through the exam prerequisites and the structure of the exam. You will then learn basic and advanced AI in Azure. Principles of responsible AI, Azure Machine Learning (ML), Azure Cognitive Services, and Bot Services are covered, followed by a practice test. You will go through ML fundamental concepts, model training, and validation along with case studies and a practice test for better preparation. The book includes the fundamentals of Azure and computer vision cognitive services. Various vision services and face services are demonstrated as well as analyzing image and text using OCR. You will understand concepts of natural language processing (NLP) such as text analysis, language modelling, entity recognition, sentiment analysis, speech recognition, and synthesis and also learn how to leverage Microsoft Azure for NLP.After reading this book, you will be able to implement various Azure AI services and prepare for the Azure AI Fundamentals certification exam, AI-900.WHAT WILL YOU LEARN* Understand AI fundamentals and responsibilities* Know the Microsoft Azure offerings for AI* Understand foundational concepts for ML and Azure offerings for ML* Understand Azure Cognitive Services such as Custom Vision, Face, Form Recognizer, Text-to-Speech, and Image AnalysisWHO THIS BOOK IS FORAzure and AI users working with ML servicesKRUNAL S. TRIVEDI is a Microsoft Certified Trainer and a Microsoft Azure MVP for the past 5 years. He has been providing technical training on a variety of Microsoft and non-Microsoft technologies to IT corporations all over the world for the past 14 years. He is an enthusiastic speaker, trainer, writer, and author. Krunal is actively involved in project architecting, building solutions using modern edge technologies such as React, Angular, Docker, and Microsoft Azure, in addition to training. He has worked on numerous projects and products, from requirement gathering to project deployment using the Agile methodology and DevOps pipeline.CHAPTER 1: AI-900 OVERVIEW OF EXAM PREPARATIONCHAPTER GOAL:The chapter introduces the exam to the learners. The exam object-IVES ARE MADE CLEAR TO THE READERS. READERS GAIN UNDERSTANDING ABOUT EXAM MODULES, MODULE WEIGHTAGE, AND HOW MUCH TO EXPECT FROM EACH MODULE THROUGHOUT THE EXAMINATION. LINKS TO PERTINENT RESOURCES ON MICROSOFT LEARN WOULD BE PROVIDED FOR THE READERS' BENEFIT.NO OF PAGES: 2SUBTOPICS1. Exam Overview2. Who is this exam for – Exam prerequisite3. Modules and weightage in exam4. Module DescriptionCHAPTER 2: FUNDAMENTALS OF ARTIFICIAL INTELLIGENCECHAPTER GOAL:The chapter's objective is to introduce some foundational, high-level elements. These concepts would be explored in depth over the next chapters of the books.NO OF PAGES: 15SUB - TOPICS1. What is Artificial Intelligence?2. Understanding Artificial Intelligence workloads3. Principles of Responsible AI4. Understanding Artificial Intelligence in Microsoft Azure5. AI Services in Microsoft Azure1. Azure Machine Learning2. Azure Cognitive Service3. Azure Bot Service4. Azure Cognitive Search6. Module Review7. Introspective Practice8. Solutions to the practice test9. References: Microsoft LearnCHAPTER 3: MACHINE LEARNING FUNDAMENTAL CONCEPTSCHAPTER GOAL: THIS CHAPTER MAKE READER FAMILIAR TO THE MACHINE LEARNING FUNDAMENTALS INTRODUCING MACHINE LEARNING, TYPES OF MACHINE LEARNING, MODEL TRAINING AND VALIDATION. HERE READERS WILL ALSO GET TO KNOW ABOUT VARIOUS TOOLS USED FOR MACHINE LEARNING.NO OF PAGES: 30SUB - TOPICS:1. What is Machine Learning?2. Describing Core Machine Learning Concepts1. Dataset, Features and Labels2. Machine Learning Algorithms in brief3. Machine Learning Workflow4. Model Evaluation Metrics3. Types of Machine Learning1. Regression2. Classification3. Clustering3. The two importance elements: Model Training and Validation4. Introducing Azure Machine Learning5. Tools for Azure Machine Learning1 Azure Machine Learning Studio2 Azure Machine Learning Designer6 What is Automated Machine Learning?7. Practical Labs:Using Azure Machine Learning Designer to build a regression model Using Azure Machine Learning Designer, create a classification modelUsing Azure Machine Learning Designer to build a clustering model8. Module Review9. Introspective Practice10. Solutions to the practice test11. References: Microsoft LearnCHAPTER 4: COMPUTER VISIONCHAPTER GOAL: THE CHAPTER INTRODUCES READERS TO THE FUNDAMENTALS OF AZURE COGNITIVE SERVICES IN BRIEF, AS WELL AS IN DEPTH KNOWLEDGE OF COMPUTER VISION COGNITIVE SERVICE.NO OF PAGES: 50SUB - TOPICS:1. Getting Started with Azure Cognitive ServiceBenefits of Cognitive ServiceAzure Cognitive Service: SpeechLanguageVisionDecisionOpen AI Service2. What is Computer Vision?3. Computer Vision Core Elements: Image Classification and Object Detection3. Computer Vision Application4. Exploring Various Vision Service1. Computer Vision2. Custom Vision3. Face4. Form Recognizer5. Understanding of OCR6. Practical Labs:* 1. Analysing image with Computer Vision* 2. Training Models with Custom Vision* 3. Using Face Service to analyse faces* 4. Analysing text with Computer Vision Service using OCR7. Introspective Practice Test8. Solutions to the practice test9. References: Microsoft LearnCHAPTER 5: FUNDAMENTALS OF NATURAL LANGUAGE PROCESSINGCHAPTER GOAL: THIS CHAPTER INTRODUCES READERS WITH THE RESPONSIBILITIES OF NATURAL LANGUAGE PROCESSING SUCH AS TEXT ANALYSIS, LANGUAGE MODELLING, ENTITY RECOGNITION, SENTIMENT ANALYSIS, SPEECH RECOGNITION AND SYNTHESIS AND HOW TO LEVERAGE MICROSOFT AZURE FOR NLP.NO. OF PAGES: 501. Getting Started with Natural Language Processing1. What is Natural Language Processing?2. Core NLP Responsibilities1. Text analysis and entity recognition2. Sentiment analysis3. Speech recognition and synthesis4. Machine Translation5. Semantic Language modelling2. AI for Conversational Interactions3. Microsoft Azure for NLP1. Core Azure NLP workloads: Language, Speech and Translator2. Language:1. Language Detection2. Key phrase extraction3. Entity Detection4. Sentiment Analysis5. Question Answering6. Conversational Language Understanding3. Speech:1. Text to speech2. Speech to text3. Speech translation4. Translator1. Text Translation2. Microsoft Azure platform for Conversational AI1. Azure Bot Service3. Practical Labs:* 1. Text analysis with text-analysis-service* 2. Using the Speech service's speech-to-text capabilities to transcribe audible speech to text. * 3. Using the Speech service's text-to-speech capabilities to generate audible speech from text. * 4. Using translator service to convert text* 5. Language Understanding Application Development* 6. Developing a Q&A generator with Azure Bot Service * 7. Provisioning chat bot using Microsoft Azure Bot Service4. Introspective Test5. Solutions to the Practice Test6. References: Microsoft Learn
Data Analytics in the AWS Cloud
A COMPREHENSIVE AND ACCESSIBLE ROADMAP TO PERFORMING DATA ANALYTICS IN THE AWS CLOUDIn Data Analytics in the AWS Cloud: Building a Data Platform for BI and Predictive Analytics on AWS, accomplished software engineer and data architect Joe Minichino delivers an expert blueprint to storing, processing, analyzing data on the Amazon Web Services cloud platform. In the book, you’ll explore every relevant aspect of data analytics—from data engineering to analysis, business intelligence, DevOps, and MLOps—as you discover how to integrate machine learning predictions with analytics engines and visualization tools. You’ll also find:* Real-world use cases of AWS architectures that demystify the applications of data analytics* Accessible introductions to data acquisition, importation, storage, visualization, and reporting* Expert insights into serverless data engineering and how to use it to reduce overhead and costs, improve stability, and simplify maintenanceA can't-miss for data architects, analysts, engineers and technical professionals, Data Analytics in the AWS Cloud will also earn a place on the bookshelves of business leaders seeking a better understanding of data analytics on the AWS cloud platform. GIONATA “JOE” MINICHINO is Principal Software Engineer and Data Architect on the Data & Analytics Team at Teamwork. He specializes in cloud computing, machine/deep learning, and artificial intelligence and designs end-to-end Amazon Web Services pipelines that move large quantities of diverse data for analysis and visualization.
AI for Retail
THE COMING OF THE AI REVOLUTION IN BRICK-AND-MORTAR RETAILIn AI for Retail: A Practical Guide to Modernize Your Retail Business with AI and Automation, Francois Chaubard, AI researcher and retail technology CEO, delivers a practical guide for integrating AI into your brick-and-mortar retail business. In the book, you’ll learn how to make your business more efficient by automating inventory management, supply chain, front-end, merchandising, pricing, loss prevention, e-commerce processes, and more.The author takes you step by step from no AI Strategy at all to implementing a robust AI playbook that will permeate through your entire organization. In this book, you will learn:* How AI works, including key terminology and fundamental AI applications in retail* How AI can be applied to the major functions of retail with detailed P&L analysis of each application* How to implement an AI strategy across your entire business to double or even triple Free Cash FlowAI for Retail is the comprehensive, hands-on blueprint for AI adoption that retail managers, executives, founders, entrepreneurs, board members, and other business leaders have been waiting for.SECTION 1 INTRODUCTION TO THE AI REVOLUTION 111 How Ai Has Revolutionized Many Other Industries over the Last 20 Years 132 The Three Myths of How AI Will Transform Retail 373 How AI Will Automate and Optimize Retail 514 Level- Setting the AI Doomsday- ism 67SECTION 2 AI THEORY 755 What Is AI? 776 From CPUs to GPUs 847 Optimization 888 Measuring AI Performance 949 AI Learning Techniques 10010 Simulators and AI 11111 OODA Loops 11612 Hierarchy of Data Maturity 12013 A “General Theory for Retail AI” 125SECTION 3 APPLICATIONS OF AI IN RETAIL 13714 The Inefficiencies in Retail Today 13915 AI for Merchandising 14316 AI for Inventory, Ordering, and Supply Chain Management 15317 AI for Replenishment and Labor Management 17718 AI for Labor Budgets and Scheduling 19319 AI for E- Commerce and Customer Service 19920 AI for Warehouse and Distribution Centers 21221 AI for Checkout 22722 AI for Pricing and Promotion 25423 Other AI Use Cases 263SECTION 4 IMPLEMENTATION 26924 Create your “AI Strategy and Road Map” 27125 Buying vs. Building AI 28526 How to Run a Proof of Concept Bake- off Effectively 29227 Transitioning to a Fact- based, Data- driven Culture 303About the Author 309Index 311
Customer-Data-Plattformen
Dieses Buch beantwortet grundlegende Fragen zu CDP, gibt einen Überblick über aktuelle CDPs und identifiziert deren Vorteile und Schwachstellen. Zudem setzt es sich mit unterschiedlichen Entwicklungen im Marketingumfeld auseinander, die starke Treiber für den Einsatz einer Customer-Data-Plattform (CDP) sind. Marketing-Entscheider sowie Verantwortliche aus den Bereichen Online-Marketing und E-Commerce erhalten Tipps, wie die passende CDP ausgewählt und implementiert werden kann. Zudem ist dieses Buch interessant für alle Entscheider, die sich damit beschäftigen, wie sie ihren Konsumenten ein besseres Kauferlebnis bieten können. Dabei geht Jonas Rashedi nicht nur auf die technischen Aspekte ein, sondern beleuchtet auch die organisationsbezogenen Voraussetzungen für die erfolgreiche Implementierung und Verwendung einer CDP. Praxisbeispiele veranschaulichen die Inhalte. This book offers an excellent introduction to the CDP category. I recommend it for anyone trying to understand what CDPs do, whether a CDP is right for their company, and how to select the right CDP. David M. Raab, Gründer und CEO des CDP Institutes
Teach Yourself VISUALLY Power BI
A COMPREHENSIVE AND FULLY VISUAL GUIDE TO MICROSOFT POWER BITeach Yourself VISUALLY Power BI collects all the resources you need to master the everyday use of Microsoft's powerful data visualization software and delivers them in a single, easy-to-use volume. Fully illustrated, step-by-step instructions are combined with crystal-clear screenshots that walk you through the basic and advanced functions of Microsoft Power BI.Teach Yourself VISUALLY Power BI offers the best visual learning techniques with complete source material about the interface and substance of Power BI, as well as:* Stepwise guidance on working with, transforming, and processing data sources* Instructions for customizing data visualizations to create informative and presentation-ready charts and graphs* Full-color, two-page tutorials on the more advanced features of Power BI, including app integrations and data access with DAXThe fastest, easiest way for visual learners to get a handle on Microsoft Power BI, Teach Yourself VISUALLY Power BI is a can't-miss resource, loaded with useful tips for newbies and experts alike.
Large-Scale Agile Frameworks
Das Buch Large-Scale Agile Frameworks bietet praktische Lösungen für die team- und funktionsübergreifende Priorisierung von Anforderungen und Dokumentation für Unternehmen. Es spiegelt das Zusammenspiel aktueller Technologietrends wie Cloud Computing und organisatorischer Anforderungen an Microservices wider. Organisationen sind zunehmend gefordert, ihre IT-Strategie an den Kundenbedürfnissen nach kundenzentrierten und serviceorientierten Produkten und Dienstleistungen auszurichten.Das Buch analysiert die besonderen Anforderungen an ein differenziertes Software-Dienstleistungsangebot und zeigt, wie agile Prinzipien zur Lösung dieser Probleme wirksam sind. Das Buch hebt auch die Bedeutung einer groß angelegten agilen Entwicklung hervor und bietet Organisationen eine Anleitung zur Transformation ihrer Struktur in Richtung einer agilen Priorisierung. Das Buch behandelt verschiedene geeignete Modelle, Methoden und agile Werkzeuge und gibt Empfehlungen zur funktionsübergreifenden Priorisierung von Anforderungen. Es berücksichtigt auch die Notwendigkeit von IT-Sicherheit und zeigt, wie diese in den gesamten agilen Entwicklungsprozess integriert werden kann.SASCHA BLOCK ist IT-Architekt und verfügt über mehrjährige Praxiserfahrung als Agile Coach in Digitalisierungsprojekten. Als Wirtschaftsinformatiker mit einem Master of Science im Studiengang IT-Management und Consulting an der Universität Hamburg kombiniert der Autor seine wissenschaftsorientierte Herangehensweise mit der Praxiserfahrung in agilen IT-Projekten, um zielgerichtet an innovativen und zukunftsorientierten Lösungen zu arbeiten. Agile Vorgehensmodelle, Konzepte und grundlegende Begriffe - Software-Releases und Release-Management - Wie Sie ein Large-Scale Agile Framework anpassen und in Ihrer Organisation einführen - Einflussfaktoren des Cloud-Trends und der Virtualisierung - Software-Architektur & IT-Security als integraler Bestandteil agiler Praxis - Design Thinking & Prototyping effektiv nutzen - Agile Infrastruktur und Agile Tools - Pragmatische Software-Architektur-Dokumentation - DevOps-Methoden und DevOps-Tools - ISO/IEC 25010 – Kriterien zur Qualität von Software - Datenqualität – Lebenselixier der Digitalisierung
Practical Business Analytics Using R and Python
This book illustrates how data can be useful in solving business problems. It explores various analytics techniques for using data to discover hidden patterns and relationships, predict future outcomes, optimize efficiency and improve the performance of organizations. You’ll learn how to analyze data by applying concepts of statistics, probability theory, and linear algebra. In this new edition, both R and Python are used to demonstrate these analyses. Practical Business Analytics Using R and Python also features new chapters covering databases, SQL, Neural networks, Text Analytics, and Natural Language Processing.Part one begins with an introduction to analytics, the foundations required to perform data analytics, and explains different analytics terms and concepts such as databases and SQL, basic statistics, probability theory, and data exploration. Part two introduces predictive models using statistical machine learning and discusses concepts like regression, classification, and neural networks. Part three covers two of the most popular unsupervised learning techniques, clustering and association mining, as well as text mining and natural language processing (NLP). The book concludes with an overview of big data analytics, R and Python essentials for analytics including libraries such as pandas and NumPy.Upon completing this book, you will understand how to improve business outcomes by leveraging R and Python for data analytics.WHAT YOU WILL LEARN* Master the mathematical foundations required for business analytics* Understand various analytics models and data mining techniques such as regression, supervised machine learning algorithms for modeling, unsupervised modeling techniques, and how to choose the correct algorithm for analysis in any given task* Use R and Python to develop descriptive models, predictive models, and optimize models* Interpret and recommend actions based on analytical model outcomesWHO THIS BOOK IS FORSoftware professionals and developers, managers, and executives who want to understand and learn the fundamentals of analytics using R and Python.DR. UMESH HODEGHATTA RAO is an engineer, a scientist, and an educator. He is currently a faculty member at Northeastern University, MA, USA, specializing in data analytics, AI, machine learning, deep learning, natural language processing (NLP), and cyber security. He has more than 25 years of work experience in technical and senior management positions at AT&T Bell Laboratories, Cisco Systems, McAfee, and Wipro. He was also a faculty member at Kent State University, Kent, Ohio, USA and Xavier Institute of Management, Bhubaneswar, India. He has his master’s degree in Electrical and Computer Engineering (ECE) from Oklahoma State University, USA and a Ph.D. from the Indian Institute of Technology (IIT), Kharagpur. His research interest is applying AI Machine Learning to strengthen an organization’s information security based on his expertise on Information Security and Machine Learning. As a Chief Data Scientist, he is helping business leaders to make informed decisions and recommendations linked to the organization's strategy and financial goals, reflecting an awareness of external dynamics based on a data-driven approach.He has published many journal articles in international journals and conference proceedings. In addition, he has authored books titled "Business Analytics Using R: A Practical Approach" and “The InfoSec Handbook: An Introduction to Information Security” published by Springer Apress, USA. Furthermore, Dr. Hodeghatta has contributed his services to many professional organizations and regulatory bodies. He was an Executive Committee member of IEEE Computer Society (India); Academic advisory member for the Information and Security Audit Association (ISACA), USA; IT advisor for the government of India; Technical Advisory Member of the International Neural Network Society (INNS) India; Advisory member of Task Force on Business Intelligence & Knowledge Management; He is listed in Who’s Who in the World in the year 2012, 2013, 2014, 2015 and 2016. He is also a senior member of the IEEE, USA.UMESHA NAYAK is a director and principal consultant of MUSA Software Engineering Pvt. Ltd. which focuses on systems/process/management consulting. He has 33 years experience, of which 12 years are in providing consulting to IT / manufacturing and other organizations from across the globe. He is a Master of Science in Software Systems; Master of Arts in Economics; CAIIB; Certified Information Systems Auditor (CISA), and Certified Risk and Information Systems Control (CRISC) professional from ISACA, US; PGDFM; Certified Ethical Hacker from EC Council; Certified Lead Auditor for many of the standards; Certified Coach among others. He has worked extensively in banking, software development, product design and development, project management, program management, information technology audits, information application audits, quality assurance, coaching, product reliability, human resource management, and consultancy. He was Vice President and Corporate Executive Council member at Polaris Software Lab, Chennai prior to his current assignment. He has also held various roles like Head of Quality, Head of SEPG and Head of Strategic Practice Unit – Risks & Treasury at Polaris Software Lab. He started his journey with computers in 1981 with ICL mainframes and continued further with minis and PCs. He was one of the founding members of the information systems auditing in the banking industry in India. He has effectively guided many organizations through successful ISO 9001/ISO 27001/CMMI and other certifications and process/product improvements. He has co-authored the open access book The InfoSec Handbook: An Introduction to Information Security, published by Apress.Section 1: Introduction to AnalyticsIn this section, we discuss the necessary foundations required to perform data analytics. We discuss different analytics terms, basics statistics and probability theory, descriptive statistics including various plots, and various measures for evaluating your predictive models.Chapter 1: Business Analytics RevolutionChapter 2: Foundations of Business AnalyticsChapter 3: Structured Query Language (SQL) AnalyticsChapter 4: Business Analytics ProcessChapter 5: Exploratory Data Analysis (EDA)Chapter 6: Evaluating Analytics Model PerformanceSection II: Supervised Learning and Predictive AnalyticsIn this section, we introduce statistical learning models and machine learning models. We present various regression analysis and classification analysis. We also discuss logistic regression and end our discussion by introducing Neural Network and gradient descent algorithms.Chapter 7: Simple Linear RegressionsChapter 8: Multiple Linear RegressionsChapter 9: ClassificationChapter 10: Neural NetworksChapter 11: Logistic RegressionSection III: Time series modelsIn this section, we introduce optimization models and Time series analysis. In time series, we discuss different forecasting models, and in optimization models, we introduce both linear and non-linear optimization models.Chapter 12: Time Series – ForecastingSection IV: Unsupervised model and Text MiningIn this section, we discuss two popular unsupervised models - cluster analysis and relationship data mining techniques. Finally, we end this section by introducing text mining and NLP and briefly introducing big data.Chapter 13: Cluster AnalysisChapter 14: Relationship Data MiningChapter 15: Mining Text and Text AnalyticsChapter 16: Big Data and Big Data AnalyticsSection V: Business Analytics ToolsThis is the last part. In this section weThis section summarizes what we have learned in the earlier section by working on some case studies. We work on practical cases using public datasets using both ‘R’ and ‘Python’.Chapter 17: R programming for AnalyticsChapter 18: Python Programming for Analytics
Besser Schreiben mit KI
KI-Technologie verändert das Schreiben rasant. Angebot: Leser:innen dieses Buchs erhalten automatisch immer die neueste Auflage. Wer sich registriert (Details im Buch, den Link darf ich hier leider nicht angeben), erhält die Updates per E-Mail. Mit KI-Tools kann fast jeder und jede korrekte, handwerklich solide Texte schreiben. Daher wird das Volumen dieser Texte sprunghaft steigen. Stellen Sie sich vor, alle 3000er in den Alpen bekommen einen Lift bis zum Gipfelkreuz. Dann laufen dort plötzlich lauter Turnschuhtouristen herum. Früher traf man so weit oben nur geübte Bergsteiger. Aber die höchsten Gipfel, zu denen keine Bergbahn führt, bleiben den durchtrainierten Alpinisten vorbehalten. Wenn Masse zunimmt wird origineller Inhalt wertvoller. Die Schere wird weiter aufgehen zwischen den fleissigen Büro-Schreiberlingen und denen, die noch wissen, wie ein Katzenklo riecht, wie Waldboden federt oder ein altersschwacher Rasenmäher klingt (und darüber schreiben können). Wer sich (als Texter:in) selbst mutig ins Gewühl stürzt, Augen und Ohren offenhält, leibhaftig in den wilden Wassern der realen Welt herumpaddelt, sich mit ähnlich Gesinnten austauscht und neugierig reflektiert, erlebt genug, um die Inhalte zu produzieren, die sich vom Mittelmass abheben. So jemand kann dann KI-Tools als Ausgangsmaterial nehmen und daraus grosses Kino machen. Dieses Buch ist eine Gemeinschaftsleistung von ChatGPT (die Kiste) und einer menschlichen Intelligenz (Matthias Wiemeyer). Diese Mischung macht den Unterschied. Ich nenne die Kiste «Kiste», damit ich sie nicht so leicht mit einem Menschen verwechsle. Menschen haben Gefühle, Erinnerungen (keine Datenspeicher), einen Körper, sinnliche Erfahrungen und sind analoge biologische «Maschinen». Menschen können sich langweilen, Fehler machen und an ihre Omi denken, wenn sie Veilchenduft riechen. Die Kiste hat Algorithmen und Datenspeicher, ermüdet nicht, erlebt nichts und empfindet nichts. Sie kann eindrucksvolle Tricks, aber sie kann nicht darauf stolz sein. Prompt Engineering Wer lernen will, bessere Texte mit KI zu schreiben, muss vor allem lernen, effektive «Prompts» zu schreiben. Wenn Sie einen «Prompt» schreiben, teilen Sie ChatGPT Ihr Anliegen mit. Denn ohne Anliegen macht die KI gar nichts. Sie gähnt nicht einmal oder dreht Däumchen. Gute Prompts zu schreiben, ist das Hauptanliegen dieses Buchs. Wenn Sie die hier vorgestellten Techniken benutzen, wird das von ChatGPT produzierte Rohmaterial um besser werden.Matthias hat Philosophie und Betriebswirtschaftslehre studiert und bereits vor der Gründung von Google mit Computern experimentiert. Später hat er als Unternehmensberater ein Buch darüber geschrieben, wie Technologie und Menschen gemeinsam Höchstleistungen erbringen. Seit 2011 lebt er vom Schreiben (Schreibszene Schweiz). Matthias ist auch Gründungspartner des Deutsch-Schweizer Medizintechnologie-Startups "Aristra", das Telemedizin und KI für bessere Diagnosen zusammenbringt.
Data Fabric and Data Mesh Approaches with AI
Understand modern data fabric and data mesh concepts using AI-based self-service data discovery and delivery capabilities, a range of intelligent data integration styles, and automated unified data governance—all designed to deliver "data as a product" within hybrid cloud landscapes.This book teaches you how to successfully deploy state-of-the-art data mesh solutions and gain a comprehensive overview on how a data fabric architecture uses artificial intelligence (AI) and machine learning (ML) for automated metadata management and self-service data discovery and consumption. You will learn how data fabric and data mesh relate to other concepts such as data DataOps, MLOps, AIDevOps, and more. Many examples are included to demonstrate how to modernize the consumption of data to enable a shopping-for-data (data as a product) experience.By the end of this book, you will understand the data fabric concept and architecture as it relates to themes such as automated unified data governance and compliance, enterprise information architecture, AI and hybrid cloud landscapes, and intelligent cataloging and metadata management.WHAT YOU WILL LEARN* Discover best practices and methods to successfully implement a data fabric architecture and data mesh solution* Understand key data fabric capabilities, e.g., self-service data discovery, intelligent data integration techniques, intelligent cataloging and metadata management, and trustworthy AI* Recognize the importance of data fabric to accelerate digital transformation and democratize data access* Dive into important data fabric topics, addressing current data fabric challenges* Conceive data fabric and data mesh concepts holistically within an enterprise context* Become acquainted with the business benefits of data fabric and data meshWHO THIS BOOK IS FORAnyone who is interested in deploying modern data fabric architectures and data mesh solutions within an enterprise, including IT and business leaders, data governance and data office professionals, data stewards and engineers, data scientists, and information and data architects. Readers should have a basic understanding of enterprise information architecture.EBERHARD HECHLER is an Executive Architect at the IBM Germany R&D Lab. He is a member of the Data and AI development organization and addresses the broader analytics scope, including machine learning (ML). After more than two years at the IBM Kingston Lab in New York, he worked in software development, performance optimization, IT/solution architecture and design, Hadoop and Spark integration, and mobile device management (MDM).Eberhard worked with Db2 on the MVS platform, focusing on testing and performance measurements. He has worked worldwide with IBM clients from various industries on a vast number of topics such as data and AI, information architectures, and industry solutions. From 2011 to 2014, he was at IBM Singapore, working as the Lead Big Data Architect in the Communications Sector of IBM’s Software Group throughout the Asia-Pacific region.Eberhard has studied in Germany and France, and holds a master’s degree (Dipl.-Math.) in Pure Mathematics and a bachelor’s degree (Dipl.-Ing. (FH)) in Electrical Engineering. He is a member of the IBM Academy of Technology, and has co-authored the following books:: Enterprise MDM, The Art of Enterprise Information Architecture, Beyond Big Data, and Deploying AI in the Enterprise (Apress).MARYELA WEIHRAUCH is an IBM Distinguished Engineer in the Data and AI development group for IBM Z Technical Sales, and is a Customer Success leader. She has extensive experience with relational databases in terms of systems, application, and database design. She is engaged with enterprises across the world and helps them adopt new data and analytics technologies. Her former roles in Db2 for z/OS development have involved determining a Db2 for z/OS strategy for HTAP (Hybrid Transaction and Analytics Processing), including the Db2 Analytics Accelerator strategy and implementation as well as Db2's application enablement strategy.Maryela consults with enterprises around the globe on many data modernization initiatives and leads an effort to develop a methodology to determine the best data architecture for a given application based on data architecture decision criteria.Maryela holds two master's degrees in Computer Science from Technical University Chemnitz, Germany and California State University, Chico, California, USA. She holds a number of patents and is a member of the IBM Academy of Technology. She frequently shares her experience at conferences around the world.YAN (CATHERINE) WU is the Program Director at the IBM Silicon Valley Lab. She is an engineering leader with deep expertise in data governance, artificial intelligence (AI), machine learning (ML), enterprise design thinking, and pragmatic product marketing. She has extensive experience working with large clients to discover use cases for data governance and AI, explore how the latest technologies can be applied to resolve real-world business challenges, and deploy these technologies to accelerate enterprise digital transformation. She has a proven track record in translating customer needs into software solutions while working collaboratively with globally distributed development, design, and offering management teams.Prior to her current position at IBM US, Catherine was the Lab Director of the Data and AI development lab at IBM China. In these roles, Catherine demonstrated her ability to think horizontally and strategically to bring teams together to create innovative solutions for complex problems.Catherine is an ambassador for the Women in Data Science organization (https://www.widsconference.org/). She is passionate about inspiring and educating data scientists worldwide, particularly women in this field. She organized WiDS regional events over the past three years.Catherine holds a master’s degree in Computer Science from National University of Singapore, and a bachelor’s degree in Computer Technology from Tsinghua University.PART I – DATA FABRIC FOUNDATIONChapter 1: Evolution of Data ArchitectureChapter 2: Terminology – Data Fabric and Data MeshChapter 3: Data Fabric and Data Mesh Use Case ScenariosChapter 4: Data Fabric and Data Mesh Business BenefitsPART II – KEY DATA FABRIC CAPABILITIES AND CONCEPTSChapter 5: Key Data Fabric and Data Mesh CapabilitiesChapter 6: Relevant AI and ML ConceptsChapter 7: AI/ML for a Data Fabric and Data MeshChapter 8: AI for Entity ResolutionChapter 9: Data Fabric and Data Mesh for the AI LifecyclePART III – DEPLOYING DATA FABRIC SOLUTIONS IN CONTEXTChapter 10: Data Fabric Architecture PatternsChapter 11: Role of Data Fabric within an Enterprise Architecture\Chapter 12: Data Fabric and Data Mesh in Hybrid Cloud LandscapeChapter 13: Intelligent Cataloging and Metadata ManagementChapter 14: Automated Data Fabric and Data Mesh AspectsChapter 15: Data Governance in the Context of Data Fabric and Data MeshPART IV – CURRENT OFFERINGS AND FUTURE ASPECTSChapter 16: Sample Vendor OfferingsChapter 17: Data Fabric and Data Mesh Research AreasChapter 18: In Summary and OnwardsAbbreviations.
Ermittlung von Fahrwerksbelastungen aus CAN-Daten
In diesem Buch werden Algorithmen entwickelt, mit denen die Fahrwerksbelastungen rechnerisch aus CAN-Daten abgeschätzt werden. Eine gute Übereinstimmung zwischen den berechneten und gemessenen Lastdaten ist nachgewiesen. Diese Algorithmen ermöglichen das dauerhafte Lastkollektiv der Radnabenkräfte und -momente im Fahrbetrieb. Somit wird z. B. eine kostengünstige Lösung zum Belastungsabgleich zwischen dem Fahrzeugdauerlauf- und Prüfstandsversuch für die Betriebsfestigkeit angeboten.Stand der Technik: Dauerhafte Belastungsermittlung im Fahrbetrieb.- Datenaufbereitung.- Ermittlung belastungsrelevanter Parameter.- Ermittlung des niederfrequenten Anteils der Fahrwerksbelastungen.- Ermittlung des hochfrequenten Anteils der Fahrwerksbelastungen.- Validierung der Algorithmen und Ermittlung der Prognosegüte.
Not with a Bug, But with a Sticker
A ROBUST AND ENGAGING ACCOUNT OF THE SINGLE GREATEST THREAT FACED BY AI AND ML SYSTEMSIn Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour – from inside secretive government organizations to academic workshops at ski chalets to Google’s cafeteria – recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes. Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits. The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competition’s AI systems. An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warning—albeit an entertaining and engaging one—we should all heed. How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer. The authors are donating the proceeds from this book to two charities: Black in AI and Bountiful Children’s Foundation.
CompTIA ITF+ CertMike: Prepare. Practice. Pass the Test! Get Certified!
THE LEADING, NO-NONSENSE GUIDE TO GET YOU UP TO SPEED ON THE FUNDAMENTALS OF ITIn CompTIA ITF+ CertMike: Prepare. Practice. Pass the Exam! Get Certified! Exam FC0-U61, experienced tech education guru Mike Chapple delivers an essential and efficient guide to acing the ITF+ (IT Fundamentals+) exam administered by CompTIA. In the book, you’ll get access to every objective tested by the foundational exam, including IT concepts and terminology, infrastructure, applications and software, software development, database fundamentals, and security. Ace the test using the proven CertMike approach:* PREPARE -- CertMike is your personal study coach, guiding you through all the exam objectives and helping you gain an understanding of how they apply to on-the-job tasks!* PRACTICE -- Each chapter includes two multiple choice practice questions. Work through the detailed explanations to evaluate each answer option and understand the reason for the best answer!* PASS -- On exam day, use the critical knowledge you've learned when you’re ready to take the test. You'll feel ready and confident to pass the exam and earn your certification!With a laser-focus on getting you job- and exam-ready, the book skips the fluff and gets right to the point of getting you familiar with IT basics and on the road to an in-demand IT certification and a new career in tech. You'll also get complimentary access to additional online study tools, complete with a bonus practice exam and audio recordings of the CertMike Exam Essentials. Banish test anxiety and feel ready to pass the test—the first time around!A must-read guide for anyone considering a career in IT and looking for a resource that assumes no background knowledge or experience, CompTIA ITF+ CertMike: Prepare. Practice. Pass the Test! Get Certified! Exam FC0-U61 is your ticket to basic IT competency and confidence.MIKE CHAPPLE, PHD is Teaching Professor of Information Technology, Analytics, and Operations at Notre Dame’s Mendoza College of Business. He is a bestselling author of over 25 books and serves as the Academic Director of the University’s Master of Science in Business Analytics program. He holds multiple additional certifications, including the CISSP (Certified Information Systems Security Professional), CySA+ (CompTIA Cybersecurity Analyst), CIPP/US (Certified Information Privacy Professional), CompTIA PenTest+, and CompTIA Security+. Mike provides cybersecurity certification resources at his website, CertMike.com.
CompTIA A+ CertMike: Prepare. Practice. Pass the Test! Get Certified!
SKIP THE FLUFF AND GET STRAIGHT TO THE ESSENTIALS WITH AN INDISPENSABLE PREP HANDBOOK FOR THE COMPTIA A+ CORE 1 EXAMIn CompTIA A+ CertMike: Prepare. Practice. Pass the Test! Get Certified!Core 1 Exam 220-1101, veteran tech experts and educators Mike Chapple and Mark Soper deliver a hands-on and practical roadmap to taking—and succeeding on—the CompTIA A+ Core 1 exam. You’ll learn how to install, configure, and maintain computer equipment, mobile devices, and software for end users, service components based on customer requirements, understand networking basics, and apply essential cybersecurity methods. Ace the test using the proven CertMike approach:* PREPARE -- CertMike is your personal study coach, guiding you through all the exam objectives and helping you gain an understanding of how they apply to on-the-job tasks!* PRACTICE -- Each chapter includes two multiple choice practice questions. Work through the detailed explanations to evaluate each answer option and understand the reason for the best answer!* PASS -- On exam day, use the critical knowledge you've learned when you’re ready to take the test. You'll feel ready and confident to pass the exam and earn your certification!With a laser-focus on getting you job- and exam-ready, the book skips the fluff and gets right to the point of getting you familiar with IT basics and on the road to an in-demand IT certification and a new career in tech. You’ll also get complimentary access to additional online study tools, complete with a bonus practice exam and audio recordings of the CertMike Exam Essentials. Banish test anxiety and feel ready to pass the test—the first time around!An indispensable resource for anyone preparing for their A+ certification, CompTIA A+ CertMike: Prepare. Practice. Pass the Test! Get Certified! Core 1 Exam 220-1101 is also a must-read for hardware and PC technicians seeking to upgrade their skillset.
Introducing .NET MAUI
Interested in giving Microsoft’s new Multi-platform App UI (MAUI) a try? This book provides developers with a comprehensive set of tools and hands-on coding to build their own cross-platform applications.The book is a comprehensive end-to-end guide on creating, building, and distributing .NET MAUI applications. As you walk through each new concept, .NET MAUI expert and Microsoft MVP Shaun Lawrence will show the concept's value and uses, and then have you apply it in a build-along application. You will work with this build-along application right up until you are ready to ship it to the relevant stores (e.g., App Store, etc.).The underlying theme through the book is to explain a key concept, show how to implement it directly in order to reinforce your understanding, and then show potential simplifications (e.g., alternative libraries) that can help you reduce the complexities of an applications code base.WHAT YOU WILL LEARN* Create a .NET MAUI application* Apply commonly required techniques* Apply more advanced techniques to make applications stand out* Know what to consider when distributing applications to the relevant stores* Take an application from concept through to productionWHO THIS BOOK IS FORDevelopers who are new to .NET MAUI and cross-platform development. A basic knowledge of C# is required, but no prior knowledge using .NET MAUI is required. Experienced developers also will find the book useful as it covers topics key to modern day development (such as accessibility, performance, and distribution). Xamarin Forms developers will find the book useful as key features new to .NET MAUI that will aid in the migration from Xamarin Forms to .NET MAUI are explained.SHAUN LAWRENCE is an experienced software engineer who has been specializing in building mobile and desktop applications for the past 15 years. He is a recognized Microsoft MVP in Development Technologies with his work helping the community learn and build with Xamarin Forms, the predecessor to .NET MAUI. His recent discovery of the value he can add by sharing his experience with others has thrust him on to the path of wanting to find any way possible to continue it.Shaun actively maintains several open-source projects within the .NET community. A key project for the scope of this book is the .NET MAUI Community Toolkit where he predominantly focuses on building good quality documentation for developers to consume. Shaun lives in the United Kingdom with his wife, two children, and their dog.Part I – Getting to Know .NET MAUIChapter 1: Introduction to .NET MAUIChapter 2: Building Our First applicationChapter 3: The Fundamentals of .NET MAUIPart II – User InterfaceChapter 4: An Architecture to Suit YouChapter 5: User Interface EssentialsChapter 6: Creating Our Own LayoutChapter 7: AccessibilityChapter 8: Advanced UI ConceptsChapter 9: Local DataPart III – Behind the ScenesChapter 10: Remote DataChapter 11: Getting SpecificPart IV – Platform SpecificsChapter 12: TestingChapter 13: Lets Get GraphicalChapter 14: Releasing Our ApplicationChapter 15: Conclusion.
Continuous Integration (CI) and Continuous Delivery (CD)
Use continuous Integration (CI) and continuous delivery (CD) to improve the speed of software delivery. This book presents a game changer—how to use pipelines to automate the software delivery process. The theories about CI/CD are much the same, but the book covers what the development of pipelines looks like and how testing of pipelines themselves should be performed.Most teams just plunge into coding, without thinking about the CI/CD process itself. Why don’t we use the same development method for pipelines that we use for apps?Pipelines code development undergoes similar stages as application code development, such as requirements analysis, development, testing, implementation, operations, and monitoring. This is the starting point of the book. It describes the current challenges with pipeline development and how this process can be improved and structured. It describes in detail how to design pipelines and shows examples in BPMN 2.0 notation.WHAT YOU’LL LEARN* Know the shortcomings and challenges of current pipeline development such as misalignment between the pipeline engineer and the team’s workflow, the use of infrastructure as code (IaC), and pipeline security* Understand the need for CI/CD requirements through the book's non-exhaustive list of more than 60 CI/CD requirements provided to inspire and increase awareness* See how certain choices affect the way a pipeline is designed (and realized)* Become familiar with branching strategy, build strategy, test strategy, release strategy, and deployment strategy that are explained in detail in the book, including their effect on pipeline design* Know how pipelines can be unit tested, using a real-world example* Know how performance bottlenecks in a pipeline occur, how they can be detected, and how they can be solved* View a complete implementation, including code, showing how the guidelines in this book are applied to a real use caseWHO THIS BOOK IS FORDevOps engineers and solution architects involved with automating the software supply chain and using application lifecycle management (ALM)/integration platforms such as Jenkins, CircleCI, Bamboo, and Azure DevOps; intermediate and experienced DevOps engineers (developers, ops engineers, test engineers); and ICT managers interested in the CI/CD pipeline development domainHENRY VAN MERODE is a Solution Architect with over 30 years of experience in ICT within several financial organizations. His experience spans a wide range of technologies and platforms, from IBM Mainframe to Cloud systems on AWS and Azure. He developed, designed, and architected major financial systems such as Internet Banking and Order Management systems, with a focus on performance, high availability, reliability, maintainability, and security. Last 8 years, Henry’s expertise has been extended with Continuous Integration, Continuous Delivery, and automated pipelines. As an Azure DevOps community lead, Henry likes to talk about this subject and promotes automating the software supply chain to the teams at his work.CHAPTER 1. THE CI/CD PITFALLChallengesCHAPTER 2. CONCEPTSPrinciplesPositioning of CI/CDApplication Lifecycle Management (ALM)CI/CD strategyNaming conventionCHAPTER 3. REQUIREMENTS ANALYSISGenericWorkflowTechnologyInformationSecurityResource constraintsManageabilityOperationsQuality AssuranceMetricsMonitoringGovernanceCHAPTER 4. PIPELINE DESIGNCI/CD and pipeline design approachBPMN 2.0BPMN elements overviewBPMN in actionLevel of detailLogical design versus realizationThe Generic CI/CD PipelineValidate entry criteriaExecute buildPerform unit testsAnalyze codePackage artifactPublish artifactProvision test environmentDeploy artifact to testPerform testValidate infrastructure compliancyValidate exit criteriaPerform dual controlProvision production environmentDeploy artifact to productionNotify actorDesign strategiesContext diagramBranching strategyTrunk-based workflowFeature branch workflowGitflowBuild strategyBuild time – Vertical scalingBuild time – Full builds versus incremental buildsBuild time – Parallel buildsBuild targetsCross-platform buildsMulti-team build strategyTest strategyAutomated versus manual testsFunctional versus non-functional testsParallel execution versus sequential executionManual tests performed by specialistsLong execution time versus short execution timeProduction deployment strategyRecreate deployment strategyBlue/green deploymentCanary testing deploymentA/B test strategySeparation of concernsDelegationApplication architectureOrchestratorEvent-based CI/CDResource constraintsParallelize stages and tasksTimeboxed deliveryCommercial of the ShelfCHAPTER 5. PIPELINE DEVELOPMENTPipeline specificationMulti-branch, multi-stage pipelineUser interface-based pipelinesScripted pipelinesDeclarative pipelinesDeclarative Jenkins pipelineDeclarative Azure DevOps pipelineRepositories - Everything as code (EaC)Development in the value streamsSimplified pipeline developmentExtended pipeline developmentAdvanced pipeline developmentDevelop a base pipelinePipeline generationPipeline of pipelines (DevOps assembly line)TriggerValidate entry criteriaExecute buildPerform unit testsAnalyze codePackage artifactPublish artifactProvision test environmentDeploy artifact to testPerform testValidate infrastructure compliancyDeploy artifact to productionNotify actorConstructsTriggersExecution environmentConnectionsConditions and conditional variablesMatrixDeployment strategyAuto-cancelOn success/failureFail fastPriorityParallelismShardsTemplatesDecoratorGates and approvalsWorkflowPluginsFeature managementThird-party libraries and containersVersioning and taggingEnvironment repositorySecrets managementSustainable pipeline developmentCHAPTER 6. TEST PIPELINESTestability of pipelinesUnit testsPerformance testsPipeline complianceAcceptance testsCHAPTER 7. PIPELINE IMPLEMENTATIONOrganizational preparationsCI/CD Infrastructure preparationsSystemSecurityTarget environment preparationsSystemSecurityPipeline preparationsRelease noteRunbookArtifact promotionCHAPTER 8. OPERATE AND MONITOROperationsMonitoringSystems monitoringPlatform monitoringSecurity monitoringShare informationEvents, alerts, incidents and notificationsREFERENCES
High-Performance Web Apps with FastAPI
Build APIs and web apps based on Asynchronous Server Gateway Interface (ASGI). This book provides a comprehensive explanation of using Pydantic models to construct the request/response objects in a FASTAPI path operation.You’ll start by reviewing type hints in Python and the asynchronous processing concepts. One of the highlights of FastAPI is its auto generation of API docs. Pydantic library is the main pillar on top of which FastAPI is built. You’ll see that ASGI has a far better performance compared to most of the other popular Python frameworks as they implement Web server Gateway Interface (WSGI), which is synchronous in nature and hence having slower response time.This book thoroughly explains how FastAPI interacts asynchronously with relational as well as NOSQL databases. Modern web apps use template engines to interact with the front-end. In this book, you will learn to use jinja2 templates and static assets. Swagger UI and OpenAPI standards are also covered in detail. Finally, different options of deployment of FastAPI app have been explored in this book.This book uses practical examples to empower you to build high performance APIsWHAT YOU'LL LEARN* Develop robust and high-performance web apps* Deploy the FastAPI app for public availability using cloud services such as Deta and Docker container* Understand the important building blocks of a web app such as form handling, templating and database interactionWHO THIS BOOK IS FORAspiring and the experienced Python developers looking to leverage the flexibility of Python and the powerful features introduced in Modern Python. Computer science Engineering students at graduate and postgraduate level will also benefit immensely from the practical approach adapted in the book.Malhar Lathkar is an independent developer, trainer, technical writer and author with over 30 years of experience. He holds a postgraduate degree in Electronics. After a brief stint as a degree college lecturer, he started his own software training and development institute. Over the years, he has gained proficiency in various programming technologies and imparted training to thousands of students and professionals from India and different countries around the world. Malhar also offers software training services to corporates. He has been associated with many EdTech companies as a freelance Subject Matter Expert. He has written a few books that have been published by well-known publishing houses.BUILD HIGH PERFORMANCE WEB APPS WITH FASTAPIChapter 1. Introduction to FastAPIChapter 2. Installation of FastAPIChapter 3. Request BodyChapter 4. TemplatesChapter 5. ResponseChapter 6. Using DatabasesChapter 7. MiddlewareChapter 8. Testing and DebuggingChapter 9. Deployment Build High Performance Web Apps with FastAPIChapter 10. Advanced Features
A11Y Unraveled
Make designing and developing accessible websites fun and straightforward by deciphering information that is often confusing. This book examines how web professionals can ensure a website is as accessible as it can be, meeting the needs of its audience.The main focus is on web accessibility and, WCAG 2.1 and 2.2 guidelines: what they are, who they are for, and what can be done from a design point of view to make the lives of the users easier. In reviewing the fundamentals, emphasis will be given on what disabilities could potentially prevent users from getting the information they need and what can be done to help them. This is achieved by breaking down web design and development terms and practices, such as web accessibility, color contrast, typography, how to design specific components like carousels, forms, and so on.Each chapter features design examples presented in a clear and concise manner. Each design element is divided into different components, highlighting exactly what helps with what, showing how a website needs to be designed for the benefit of its people. A11Y Unraveled also reviews the current laws and legislations that govern web accessibility in different parts of the world.WHAT YOU'LL LEARN* Discover how people perceive information on the web, and how that might create barriers in communication.* Review different disabilities or limitations that prevent users from accessing web information and how to address them.* Design an accessible website for specific disabilities through practical examples.* Understand how different web design components affect the user.* Study current web accessibility legislation, avoiding difficult to understand lingo.WHO THIS BOOK IS FORMain audience would be digital and web professionals (mainly designers but developers can benefit as well). It can also help business owners who want to ensure their websites are adhere to accessibility standards.Dimitris is originally from Greece and has been living in the UK for about 8 years now. He started working as a graphic designer around 2004 doing mostly print work, had his own business along the way and he is now working as a senior designer on web and digital products. He considers himself a hobbyist designer, since he has not been formally educated in the subject (he holds a degree in Geography and now finishing a degree in Biology). However, Dimitri does love all things about design and has managed to make his hobby into a profession, so he considers that a win.Dimitris likes to think that the fact he is interested in multiple subjects allows for a more spherical, multivariate-variate approach to solving (design) problems, and natural curiosity is one of the main reasons he decided to write this book. While working as a designer he always thought to himself “why do I do this”, “does it matter”, “how will this/that affect usage” so when he started learning about web accessibility, he naturally went in there 100% ready to make sense of it all. Combine that with the fact that he was appointed as the main accessibility contact in the company he works for, he had to educate himself on the subject. Now, Dimitris would like to share what he has learnt and make digital professionals see that it’s actually pretty easy to make something accessible.A11Y UNRAVELEDChapter 1: When the amazon was nothing but a riverChapter 2: Be a designer they said. It'll be fun they saidChapter 3: One standard at a timeChapter 4: How do people perceive content?Chapter 5: Tell me what to do! Designing for users with disabilitiesChapter 6: How do I know I'm doing it right?Chapter 7: But do I have to?Chapter 8: What is usability?Chapter 9: Accessibility and usability. A love affairChapter 10: Who are we designing for?Chapter 11: You can't tell me what to do. I'm an adult!Chapter 12: Now you see me, now you don'tChapter 13: Click me like you mean it
Data-Driven SEO with Python
Solve SEO problems using data science. This hands-on book is packed with Python code and data science techniques to help you generate data-driven recommendations and automate the SEO workload. This book is a practical, modern introduction to data science in the SEO context using Python. With social media, mobile, changing search engine algorithms, and ever-increasing expectations of users for super web experiences, too much data is generated for an SEO professional to make sense of in spreadsheets. For any modern-day SEO professional to succeed, it is relevant to find an alternate solution, and data science equips SEOs to grasp the issue at hand and solve it. From machine learning to Natural Language Processing (NLP) techniques, Data-Driven SEO with Python provides tried and tested techniques with full explanations for solving both everyday and complex SEO problems. This book is ideal for SEO professionals who want to take their industry skills to the next level and enhance their business value, whether they are a new starter or highly experienced in SEO, Python programming, or both. What You'll Learn See how data science works in the SEO contextThink about SEO challenges in a data driven wayApply the range of data science techniques to solve SEO issuesUnderstand site migration and relaunches are Who This Book Is For SEO practitioners, either at the department head level or all the way to the new career starter looking to improve their skills. Readers should have basic knowledge of Python to perform tasks like querying an API with some data exploration and visualization. Chapter 1: Meeting the Challenges of SEO with Data.- Chapter 2: Keyword Research.- Chapter 3: Technical.- Chapter 4: Content & UX.- Chapter 5: Authority.- Chapter 6: Competitors.- Chapter 7: Experiments.- Chapter 8: Dashboards.- Chapter 9: Site Migrations and Relaunches.- Chapter 10: Google Updates.- Chapter 11: The Future of SEO.- Chapter 12: Glossary.
Bayesian Optimization
This book covers the essential theory and implementation of popular Bayesian optimization techniques in an intuitive and well-illustrated manner. The techniques covered in this book will enable you to better tune the hyperparemeters of your machine learning models and learn sample-efficient approaches to global optimization.The book begins by introducing different Bayesian Optimization (BO) techniques, covering both commonly used tools and advanced topics. It follows a “develop from scratch” method using Python, and gradually builds up to more advanced libraries such as BoTorch, an open-source project introduced by Facebook recently. Along the way, you’ll see practical implementations of this important discipline along with thorough coverage and straightforward explanations of essential theories. This book intends to bridge the gap between researchers and practitioners, providing both with a comprehensive, easy-to-digest, and useful reference guide.After completing this book, you will have a firm grasp of Bayesian optimization techniques, which you’ll be able to put into practice in your own machine learning models.WHAT YOU WILL LEARN* Apply Bayesian Optimization to build better machine learning models* Understand and research existing and new Bayesian Optimization techniques* Leverage high-performance libraries such as BoTorch, which offer you the ability to dig into and edit the inner working* Dig into the inner workings of common optimization algorithms used to guide the search process in Bayesian optimizationWHO THIS BOOK IS FORBeginner to intermediate level professionals in machine learning, analytics or other roles relevant in data science.PENG LIU is an assistant professor of quantitative finance (practice) at Singapore Management University and an adjunct researcher at the National University of Singapore. He holds a Ph.D. in statistics from the National University of Singapore and has ten years of working experience as a data scientist across the banking, technology, and hospitality industries● Chapter 1: Bayesian Optimization in a Nutshello Chapter goal: introducing Bayesian Optimization workflow and key conceptso Estimate number of pages: 30o Sub topics:▪ What and why of Bayesian Optimization▪ Key components in Bayesian Optimization process▪ Common Bayesian Optimization applications● Chapter 2: Bayesian Optimization in Hyperparameter Tuningo Chapter goal: Showcase using Bayesian Optimization for hyperparameter tuning in training better ML modelso Estimate number of pages: 35o Sub topics:▪ ML workflow▪ Common hyperparameter tuning techniques▪ Advantage of Bayesian Optimization in tuning hyperparameters for ML models through practical examples● Chapter 3 : Gaussian Processo Chapter goal: Introduce Gaussian process and its role in Bayesian Optimization workflowo Estimate number of pages: 30o Sub topics:▪ Gaussian process breakdown▪ Theory illustration on Gaussian process▪ Coding Gaussian process as surrogate model in Bayesian Optimization● Chapter 4 : Common Acquisition Functiono Chapter goal: Introduce popular acquisition functions including EI, PI and otherso Estimate number of pages: 35o Sub topics:▪ The role of acquisition function in Bayesian Optimization▪ Theoretical basics for each common AF▪ Coding examples● Chapter 5: Advanced Acquisition Functiono Chapter goal: Introduce advanced acquisition functions including KG and PE and parallel variantso Estimate number of pages: 35o Sub topics:▪ Theoretical basics for advanced AF▪ Coding examples● Chapter 6 : Introducing BoTorcho Chapter goal: Introduce the recent GPU based package for running Bayesian Optimizationo Estimate number of pages: 40o Sub topics:▪ Introduction of the package and key components▪ Starting examples▪ Advanced examples● Chapter 7 : Case studyo Chapter goal: Demonstrate full working examples using Bayesian Optimization and BoTorcho Estimate number of pages: 30o Sub topics:▪ Two full coding examples TBD● Chapter 8 : Exotic Bayesian Optimization Problemso Chapter goal: Introduce additional Bayesian Optimization variants such as adding constraints and getting noisy observationso Estimate number of pages: 30o Sub topics:▪ Constrained Bayesian Optimization▪ Parallel Bayesian Optimization▪ BO with noisy observations▪ Look ahead Bayesian Optimization
Modern C++ for Absolute Beginners
Learn the C++ programming language in a structured, straightforward, and friendly manner. This book teaches the basics of the modern C++ programming language, the C++ Standard Library, and modern C++ standards, including C++23. No previous programming experience is required.C++ is a language like no other, surprising in its complexity, yet wonderfully sleek and elegant in so many ways. It is also a language that cannot be learned by guessing, one that is easy to get wrong and challenging to get right. To overcome this, each section is filled with real-world examples that gradually increase in complexity. Modern C++ for Absolute Beginners, Second Edition teaches more than just programming in C++23. It provides a solid C++ foundation to build upon.The author takes you through the C++ programming language, the Standard Library, and C++11 to C++23 standard basics. Each chapter is accompanied by the right amount of theory and plenty of source code examples. You will work with C++23 features and standards, yet you will also compare and take a look into previous versions of C++.After reading this book, you'll be able to start programming in modern C++ standards. You will do so with plenty of relevant source code examples, freely available via a dedicated GitHub repository.WHAT YOU WILL LEARN* Get Introduced to modern C++ in a friendly but effective way* Work with the basics of C++: types, operators, variables, constants, expressions, references, functions, classes, I/O, smart pointers, polymorphism, and more* Set up the Visual Studio environment on Windows and GCC on Linux, where you can write your own code* Declare and define functions, classes, and objects, and organize code into namespaces* Discover object-oriented programming: classes and objects, encapsulation, inheritance, polymorphism, and more using the most advanced C++ features* Employ best practices in organizing source code and controlling program workflow* Get familiar with C++ language do's and don'ts, and more* Manage the basics of lambdas, inheritance, polymorphism, smart pointers, templates, modules, contracts, concepts, and moreWHO THIS BOOK IS FORBeginner or novice programmers who wish to learn C++ programming. No prior programming experience is required.SLOBODAN DMITROVIĆ is a software consultant, trainer, and author of several programming books. He is a professional R&D software developer with two decades of experience in the industry. Slobodan provides C++ training courses for corporate clients and academic institutions.1. Introduction2. What is C++?3. C++ Compilers4. Our First Program5. Types6. Exercises7. Operators8. Standard Input9. Exercises10. Arrays11. Pointers12. References13. Introduction to Strings14. Automatic Type Deduction15. Exercises16. Statements17. Constants18. Exercises19. Functions20. Exercises21. Scope and Lifetime22. Exercises23. Classes - Introduction24. Exercises25. Classes – Inheritance and Polymorphism26. Exercises27. The static Specifier28. Templates29. Enumerations30. Exercises31. Organizing code32. Exercises33. Conversions34. Exceptions35. Smart Pointers36. Exercises37. Input/Output Streams38. C++ Standard Library and Friends39. Exercises40. C++ Standards41. Projects
The Business Manager's Guide to Software Projects
Every day, successful software projects scale and sustain businesses of all sizes and across all industries. Unfortunately, the reality is that many software projects still fail. The reasons behind these failures are seldom due to the underlying technology. Misunderstandings and communication barriers lead to wrong decisions, missed opportunities, communication breakdowns, or worse—huge economic loss. In this digitally connected world, business professionals can’t afford to be hands-off on technical projects, but they also can’t be expected to have technical certifications. They have first-hand knowledge of the business processes, are subject matter experts in software requirements, and they finance the projects. Even C-level management or board members need to rapidly gain just enough understanding of technology to make mission-critical decisions for businesses to survive and flourish. In most software projects the number of non-technical stakeholders far exceeds the numberof techies. This book distills the world of software projects into simple terms and relatable metaphors for even the most technically adverse reader. Real-life examples, entertaining analogies, and hand-drawn illustrations will stick with readers throughout their own software projects, bolstering their success. Business requirements, use cases, process flows—the list goes on. It’s all broken down in this game-changing book aimed at delivering for business and tech teams what DevOps has done for developers and operations. What You Will Learn * Know the importance of good business requirements and how to write them * Identify the most important business roles, key decisions, and critical activities involved in software projects * Strengthen collaboration between non-technical and technical teams * Grasp common software project terminology, required for non-techies * Understand the software development life cycle * Gain insight on the common software project methodologies and how they differ * Understand what software developers do at a high level Who This Book Is For Non-technical business professionals (such as small business owners, startup founders, or employees of a business of any size or industry) who need to secure and implement a software solution. The reader may supervise or collaborate with technical teams, and may be a (beginning) software developer looking for practical insights and better ways to communicate with business colleagues. Part I: Conceptual Guide.- Chapter 1: Architecture and Construction.- Chapter 2: Planning and Scope.- Chapter 3: Teething Troubles.- Chapter 4: Greenfield Construction.- Chapter 5: Laying the Right Foundation.- Chapter 6: Renovating and Extending.- Chapter 7: Technical Debt.- Chapter 8: Maintenance.- Chapter 9: Differences Between Physical Construction and Software Development.- Chapter 10: More Metaphors.- Part II: Practical Guide.- Chapter 11: The Practical Side.- Chapter 12: Plan and Prepare.- Chapter 13: Define.- Chapter 14: Develop.- Chapter 15: Test.- Chapter 16: Training, Going Live, and Maintenance.- Part III: Technical Guide.- Chapter 17: The Technical Side.- Chapter 18: Coding and Design.- Chapter 19: Metaphors for Technical Terms.- Chapter 20: Tricky Areas in Technical Development.- Chapter 21: To Sum Up.- Appendix A: Collaboration.- Appendix B: Glossary.- Appendix C: References and Further Reading.
Azure SQL Hyperscale Revealed
Take a deep dive into the Azure SQL Database Hyperscale Service Tier and discover a new form of cloud architecture from Microsoft that supports massive databases. The new horizontally scalable architecture, formerly code-named Socrates, allows you to decouple compute nodes from storage layers. This radically different approach dramatically increases the scalability of the service. This book shows you how to leverage Hyperscale to provide next-level scalability, high throughput, and fast performance from large databases in your environment.The book begins by showing how Hyperscale helps you eliminate many of the problems of traditional high-availability and disaster recovery architecture. You’ll learn how Hyperscale overcomes storage capacity limitations and issues with scale-up times and costs. With Hyperscale, your costs do not increase linearly with database size and you can manage more data than ever at a lower cost.The book teaches you how to deploy, configure, and monitor an Azure SQL Hyperscale database in a production environment. The book also covers migrating your current workloads from traditional architecture to Azure SQL Hyperscale.WHAT YOU WILL LEARN* Understand the advantages of Hyperscale over traditional architecture* Deploy a Hyperscale database on the Azure cloud (interactively and with code)* Configure the advanced features of the Hyperscale database tier* Monitor and scale database performance to suit your needs* Back up and restore your Azure SQL Hyperscale databases* Implement disaster recovery and failover capability* Compare performance of Hyperscale vs traditional architecture* Migrate existing databases to the Hyperscale service tierWHO THIS BOOK IS FORSQL architects, data engineers, and DBAs who want the most efficient and cost-effective cloud technologies to run their critical data workloads, and those seeking rapid scalability and high performance and throughput while utilizing large databasesZORAN BARAĆ is a cloud architect and data specialist with more than 15 years of hands-on experience in data optimization, administration, and architecture. He is a Certified Microsoft Trainer (MCT) and Microsoft Certified Solutions Expert (MCSE) with a master‘s degree in Information Technology. Sharing knowledge and contributing to the SQL Server community is his passion. He is also an organizer of the Auckland SQL User Meetup Group, an active blogger, and speaker at different SQL events such as Data Summits, SQL Saturdays, SQL Fridays, Meetups, etc.DANIEL SCOTT-RAYNSFORD is a Partner Technology Strategist at Microsoft with 15 years of experience as a software developer and solution architect. He specializes in DevOps and continuous delivery practices. He was a Microsoft MVP in Cloud and Datacenter Management for three years before joining Microsoft and is an active PowerShell open source contributor and Microsoft DSC Community Committee member. He is also a contributor to the Azure Architecture Center on multi-tenant architecture practices.IntroductionPART I. ARCHITECTURE.1. The Journey to Hyperscale Architecture in Azure SQL2. Azure SQL Hyperscale Architecture: Concepts and FoundationsPART II. PLANNING AND DEPLOYMENT3. Planning an Azure SQL DB Hyperscale Environment4. Deploying a Highly Available Hyperscale Database into a Virtual Network5. Administering a Hyperscale Database in a Virtual Network in the Azure Portal6. Configuring Transparent Data Encryption to Bring Your Own Key7. Enabling Geo-replication for Disaster Recovery8. Configuring Security Features and Enabling Diagnostic and Audit Logs9. Deploying Azure SQL DB Hyperscale using PowerShell10. Deploying Azure SQL DB Hyperscale using Bash and Azure CLI11. Deploying Azure SQL DB Hyperscale using Azure Bicep12. Testing Hyperscale Database Performance Against Other Azure SQL Deployment OptionsPART III. OPERATION AND MANAGEMENT13. Monitoring and Scaling14. Backup, Restore and Disaster Recovery15. Security and Updating16. Managing CostsPART IV. MIGRATION17. Determining whether Hyperscale is Appropriate18. Migrating to Hyperscale19. Reverse Migrating Away from HyperscaleConclusion
The Service-Oriented Enterprise
A service-oriented architecture is fundamental to many new IT applications, from web development to social software and cloud computing. The same principles can be applied to every aspect of the service-oriented enterprise – not just in IT. In this book, you’ll explore how an enterprise architecture and viable services can link together to create a simpler yet far more powerful view of the enterprise, as a dynamic, unified whole.You can use the ideas, principles and methods described here in business transformation, workflow mapping, system design and much else besides, in every type of enterprise - including those in which there may be little or no IT at all. Step by step, you’ll walk through the basics of service-oriented architectures, the four key categories of services and how they connect, and how all of this comes together in real-world service design, implementation and operations.From this, you’ll discover how to identify and describe the different types of services that you need for your enterprise, and how to distinguish between the services that you can safely outsource, versus those that you do need to keep in-house. By the end of this book, you’ll learn how to construct function models and service models of your enterprise as a base for service-mapping, and how to pinpoint and map the information flows you need for service-management and service-performance, to keep everything on-track to purpose.WHAT YOU'LL LEARN* See how an enterprise architecture can work as a literal architecture * Understand Stafford Beer’s "Viable System Model" and adapt it as a robust model* Study how a Viable Services Model provides a template for service design that covers functionals, non-functionals and operational governance for servicesWHO THIS BOOK IS FOREnterprise architects, Business architects, Service designers, Workflow designersTom Graves has been an independent consultant for more than four decades, in business transformation, enterprise architecture and knowledge management. His clients in Europe, Australasia and the Americas cover a broad range of industries including small-business, banking, utilities, manufacturing, logistics, engineering, media, telecoms, research, defence and government. He has a special interest in whole-enterprise architectures for non-profit, social, government and commercial enterprises.Introduction:CHAPTER GOAL: Introduce the book as a whole, summarising purpose, audience, book structure and contentNO OF PAGES 2Chapter 1: Basics – An overviewCHAPTER GOAL: Provide an outline and summary for the ‘Basics’ section, which covers background themes needed before we get into the detail about services and service-design.NO OF PAGES 2This brief chapter provides a quick overview for the role and purpose of each chapter in the ‘Basics’ section. These include the nature and business-purpose of enterprise architecture; the definition and role of a service-oriented architecture, particularly in context of enterprise architecture; and the importance of metaphor in making sense of architectures and services.Chapter 2: Basics – Enterprise ArchitectureCHAPTER GOAL: Explain the business role of enterprise-architectureNO OF PAGES: 8This chapter answers key questions about enterprise architecture, including: what it is, and where it fits within the business context; the scope of enterprise architecture, whether centred around IT, or further, towards a literal ‘the architecture of the enterprise’; and its business purpose, particularly in relation to a service-oriented view of the organization and its businessChapter 3: Basics – Service-Oriented ArchitectureCHAPTER GOAL: Summarise what ‘service-oriented’ means, for enterprise architecture practiceNO OF PAGES : 12This chapter takes us through the usual IT-oriented view of ‘service-oriented architecture’, then opens up the perspective to include all types of services, whether IT-based, machine-based or people-based. Ee build upward from a set of key definitional criteria: loosely-coupled, contract-based, discoverable, abstractions, reusable and composable, and interchangeable. Topics also include security, service-management, and the core principle of ‘everything is a service’.Chapter 4: Basics – A Matter Of MetaphorCHAPTER GOAL: Introduce the importance of metaphor in architectures – particular the contrast between ‘organisation as machine’ versus ‘organisation as organism’.NO OF PAGES: 10This chapter takes us through the practical implications of the common metaphor of ‘organisation as machine’, contrasted with the metaphor of ‘organisation as living organism’. We explore why the latter metaphor is essential for making sense of services, particularly for any services that engage with people.Chapter 5: Principles – An OverviewCHAPTER GOAL: Provide an overview and summary for the ‘’Principles’ section, which describes the structural detail underpinning a service-oriented architecture and enterprise.NO OF PAGES: 2This brief chapter provides a quick overview for the role and purpose of each chapter in the ‘Principles’ section. The chapters cover topics such as the key conceptual structure for ‘viable services’; services that deliver the core value; linked services that provide management support for delivery; services that guide end-to-end coordination; linked services that support governance and other non-functionals; and also properties and patterns from systems-theory to use in service-design.Chapter 6: Principles – The Structure Of ServicesCHAPTER GOAL: Introduce Stafford Beer’s ‘Viable System Model’, and show how it provides a consistent pattern for service-design as ‘viable services’.NO OF PAGES: 15This chapter links the Viable System Model to the machine-metaphor, and then re-forms it to align with the living-organisam metaphor as ‘viable services. Themes include the ‘brain versus brawn’ concept in the machine-metaphor; the service-relationships – both human and technical – for the living-organisam metaphor; and a new perspective on services as ‘viable systems’.Chapter 7: Principles – Delivery ServicesCHAPTER GOAL: Explore the nature and role of ‘delivery services’ – those that directly delivery value for the enterprise.NO OF PAGES: 9This chapter describes the ‘delivery services’ elements in the viable-services model. It presents the various sub-types, such as value-chain, internal support-services and infrastructure, and the interfaces that each service will need to provide.Chapter 8: Principles – Management ServicesCHAPTER GOAL: Explore the nature and role of ‘management services’ – those that provide strategy and guidance for other services.NO OF PAGES: 17This chapter describes the ‘management service’ (or ‘guidance service’) elements in the viable-services model. It presents the various sub-types, such as identity, policy and purpose; strategy-services; and tactical and run-time direction; and also the interactions and interfaces for each of these service-types.Chapter 9: Principles – Coordination ServicesCHAPTER GOAL: Explore the nature and role of ‘coordination services’ – those that guide connection and choreography between other servicesNO OF PAGES: 11This chapter describes the ‘coordination-service’ elements in the viable-services model that bridge across the silos and support the choreography of end-to-end value-chains. It present the various sub-types, in roles such as ‘develop the business’, ‘change the business’ and ‘run the business’, and the interfaces that connect between them.Chapter 10: Principles – Pervasive ServicesCHAPTER GOAL: Explore the nature and role of of ‘pervasive-services’ – those that carry the qualitative non-functionals for which every in the enterprise is responsible.NO OF PAGES: 9This chapter describes the ‘pervasive-service’ element in the viable-services model that connect to and extend the topmost policy, vision and values through to every part of the extended enterprise. It presents the various sub-types, such as awareness, skills and competency development, and verificiation and audit, and the interfaces that connect these to other services.Chapter 11: Principles – Properties And PatternsCHAPTER GOAL: Introduce the core concept of ‘service as a system’, and the properties and patterns that make this possible to implement in practiceNO OF PAGES: 18This chapter describes the key connections between service-design and systems-theory. It also explores core concerns such as service-quality, service-interdependence and service-completeness.Chapter 12: Practice – An OverviewCHAPTER GOAL: Provide an overview and summary for the ‘Practice’ section of the book, which shows how all the various elements will fit together as a unified wholeNO OF PAGES: 3This brief chapter provides and overview for the role and purpose of each chapter in the ‘Practice’ section. The chapters show how services need to link together and support each other as a five-part network, connecting purpose, people, preparation, process and performance.Chapter 13: Practice – Service PurposeCHAPTER GOAL: Show why a clear definition of service purpose is essential as an anchor for design, and how to identify that purposeNO OF PAGES: 10This chapter describes what a service purpose is, why it’s important, how to derive it, and how to use it in design and operation. To support practice, the chapter includes detailed checklists for themes such as enterprise as service, stakeholders, stakeholder-imbalance, vision and values, policies and constraints, mission and service, mission and metrics, and staying on-purpose.Chapter 14: Practice – Services And FunctionsCHAPTER GOAL: Show how to create and use a Function Model to identify and define the roles of services, the relationships between them and the people they serve.NO OF PAGES: 15This chapter describes what a Function Model is, and how to create and use it in whole-of-enterprise service design. To support practice, the chapter includes real-world examples and full step-by-step instructions and guidance on how to create and verify the model.Chapter 15: Practice – The Knowledge Of ServicesCHAPTER GOAL: Show to use the Function Model with overlays and crossmaps to guide change and verify service value and viability.NO OF PAGES: 11This chapter describes a suite of overlays for the Function Model, such as activity-based costing, single-source-of-truth, service-overlaps and more. It also provides checklists to assist in verifying viability.Chapter 16: Practice – Services In ActionCHAPTER GOAL: EXPLORE HOW TO SET UP SERVICE-CHOREOGRAPHY, PARTICULARLY PEOPLE ARE DOING DELIVERY OF THE SERVICE.NO OF PAGES: 14This chapter provides guidance, checklists and worked examples on how to tackle process-choreography for services, whether IT-based or human-based. It also provides guidance on why an over-focus on IT can be problematic in many business contexts, and what to do to break out of the IT-centric box.Chapter 17: Practice – Optimising ServicesCHAPTER GOAL: Show how to guide continual-improvement for services, and to audit and verify the continuing viability of those services.NO OF PAGES: 8This chapter shows how to use audits, after-action reviews and stakeholder-engagement to guide continual improvement and optimization of service. It includes checklists and guidance on each of those themes.Appendix A: GlossaryCHAPTER GOAL: Provide a glossary of terms used in the books.NO OF PAGES: 4Appendix B: ResourcesCHAPTER GOAL: Provide a list of books, websites and other resources referenced in the book.NO OF PAGES: 4