Allgemein
Optimierungsmethoden
Das Buch gibt eine breite Übersicht über die wichtigsten Optimierungsmethoden, wobei die Verfahren beispielhaft erläutert und mit über 400 Abbildungen illustriert werden. Im ersten Teil des Buches werden verschiedene Klassen von Optimierungsproblemen vorgestellt. Gegenstand des zweiten Teils sind klassische Methoden zur Lösung von Optimierungsproblemen. Im dritten Teil werden naturanaloge Optimierungsmethoden behandelt, darunter physikbasierende Algorithmen, evolutionäre Algorithmen, schwarmintelligente Methoden sowie Optimierungsverfahren, die durch das Immunsystem inspiriert sind. Der letzte Teil des Buches befasst sich mit der Optimierung neuronaler Netze und gibt eine Einführung in ein neues vielversprechendes Forschungsgebiet der KI-basierten, selbstlernenden Optimierungsalgorithmen. PROF. DR. RALF HOLLSTEIN lehrte an der Universität Paderborn und bis zu seiner Emeritierung an der TH Bingen im Bereich Mathematik und Computational Intelligence. Klassen von Optimierungsproblemen - Klassische Optimierungsmethoden - Naturanaloge Optimierungen - Optimierung von neuronalen Netzen - Neuronale kombinatorische Optimierung
Digital Transformation and Public Policies
The extent of digitalization and the use of digital tools no longer need to be demonstrated. While companies have been integrating the challenges of such a transformation for more than 20 years, the public sector is lagging behind.Digital Transformation and Public Policies studies the mechanisms of the digital transformation of public organizations. It explores how this new deal, driven mainly by platforms, resonates with new public policies and how digital technology is redrawing the relationship between the governors and the governed.This book, the result of transdisciplinary collaboration between researchers, aims to answer these questions by focusing on several cases: public innovation policies, health data and social policies with fiscal microsimulation devices. Valérie Revest is Professor of Economics at the Université Jean Moulin Lyon 3, iaelyon School of Management – Magellan, France. Her research focuses on the financing of innovation, digital platforms and the transformation of public innovation policies.Isabelle Liotard is a lecturer in economics at the Université Sorbonne Paris Nord – CEPN, France. Her research focuses on the digital economy, innovation and the effects of digital transformation on companies and the public sector.
Cybercrime During the SARS-CoV-2 Pandemic
The SARS-CoV-2 pandemic has had an undeniable impact on cybercrime. The initial crisis quickly became a global catastrophe with multiple consequences in economics, health, and political and social fields. This book explores how this global emergency has influenced cybercrime. Indeed, since feeding off new vulnerabilities, thanks to the effects of the pandemic crisis in various states around the world, cybercrime has increased and evolved.In 2020, the world was already dealing with numerous tensions and the effects of the global crisis have therefore only tended to exacerbate the issues that relate to cybercrime. For example, radicalization and identity theft has found an environment in which they thrive: the Internet. Criminals have been able to adapt their modus operandi, their targets and their attack vectors. However, on the plus side, the response of law enforcement and public authorities, in terms of the legal, policing and policy side of cybercrime, has also been adapted in order to better combat the increase in this phenomenon. Daniel Ventre has a PhD in Political Science and conducts his research at the CESDIP laboratory, CNRS, Université Paris Saclay, France. His work focuses on cybersecurity and cyberdefense policies.Hugo Loiseau has a PhD in Political Science and is a professor at l’École de politique appliquée at the Université de Sherbrooke, Canada. His research focuses on the political and international issues involving cybersecurity.
Google Cloud Platform (GCP) Professional Cloud Network Engineer Certification Companion
While many guides exist to help software engineers learn cloud networking design and architecture concepts, and even prepare for cloud network certifications on AWS and Azure, far fewer resources are available covering the Google Cloud Platform (GCP) Professional Cloud Network Engineer certification exam. Well, look no further! This self-paced guide book is designed to help engineers learn cloud networking best practices on GCP, and prepare for the GCP Professional Cloud Network Engineer certification exam.You will waste no time when you use this study companion. It lets you dive in and learn how GCP differs from other public cloud providers (AWS and Microsoft Azure). You will understand GCP's unique ability to allow virtual private clouds (VPCs) that span across multiple regions. You will know how to leverage GCP as a competitive advantage in the IT engineering community. Key concepts covered on the exam are called out and applied in each chapter of this book, giving you both practice and reinforcement, a far more effective learning tool than rote learning or similar approaches typically enlisted in exam preparation.Enterprises are looking for developers with Google networking skills. Now is the time to skill up! This book shows you how to leverage GCP’s developer-focused, user-friendly approach to understand how the networking components enabling the popular 1B-user Google products (e.g., Gmail, Google Search, YouTube, Google Workspace (formerly G-Suite), Google Maps, Google Photos, and many others) work behind the scenes.WHAT YOU WILL LEARNIn addition to preparing for the GCP Professional Cloud Network Engineer certification exam, you will learn how to:* Architect and design a virtual private cloud* Implement a virtual private cloud* Configure network services* Implement hybrid connectivity* Implement network security* Manage network operations* Optimize network resourcesWHO THIS BOOK IS FORSoftware engineers (network, DevOps, SecOps, DataOps, engineers skilled with SDLC), software architects (solution, security, data, infrastructure, cloud, those skilled with TOGAF), and IT professionals. Prerequisites: While this study companion is intended to be self-contained, a basic knowledge of cloud computing along with hands-on experience with a minimum of two modern programming languages (Java, C#) is beneficial in order for readers to fully achieve the objectives of the book.DARIO CABIANCA is a computer scientist (PhD, University of Milan), author, and Cloud Architect. He has worked with a variety of global enterprises for more than two decades and possesses more than 11 cloud certifications. He used his own fail-proof techniques to prepare and pass GCP, Azure, and AWS exams. He is excited to share his knowledge to help readers of his study companion book prepare for the GCP Professional Cloud Network Engineer certification exam, and also come away equipped with the necessary tools and knowledge to be confident and successful on the job.1. Exam Overview1.1. Exam Subject Areas1.2. Exam Format1.3. Supplemental Study Materials1.4. Sign up for a Free Tier1.5. Register for the Exam1.5.1. Schedule the Exam1.5.2. Rescheduling and Cancellation Policy1.5.3. Exam Results1.5.4. Retake Policy1.6. Summary2. Designing, planning, and prototyping a Google Cloud network2.1. Designing an overall network architecture2.1.1. High availability, failover, and disaster recovery strategies2.1.2. DNS strategy (e.g., on-premises, Cloud DNS)2.1.3. Security and data exfiltration requirements2.1.4. Load balancing2.1.5. Applying quotas per project and per VPC2.1.6. Hybrid connectivity (e.g., Google private access for hybrid connectivity)2.1.7. Container networking2.1.8. SaaS, PaaS, and IaaS services2.2. Designing Virtual Private Cloud (VPC) instances2.2.1. VPC Specifications2.2.2. Subnets2.2.3. IP address management and brin your own IP (BYOIP)2.2.4. Standalone vs. Shared VPC2.2.5. Multiple vs. single2.2.6. Regional vs. multi-regional2.2.7. VPC Network Peering2.2.8. Firewalls (e.g., service account-based, tag-based)2.2.9. Custom routes2.3. Designing a hybrid and multi-cloud network2.3.1. Drivers for Hybrid and Multi-cloud strategy2.3.2. Overall goals2.3.3. Designing a Hybrid and Multi-cloud strategy2.3.4. Dedicated Interconnect vs. Partner Interconnect2.3.5. Direct vs. Carrier Peering2.3.6. IPsec VPN2.3.7. Bandwidth and constraints provided by hybrid connectivity solutions2.3.8. Cloud Router2.3.9. Multi-cloud and Hybrid topologies2.3.10. Regional vs. global VPC routing mode2.3.11. Failover and Disaster Recovery strategy2.3.12. Accessing Google Services/APIs privately from on-premises locations2.3.13. IP address management across on-premises locations and cloud2.4. Designing an IP addressing plan for Google Kubernetes Engine2.4.1. GKE VPC-native clusters2.4.2. Optimizing GKE IP ranges2.4.3. Expanding GKE IP ranges2.4.4. Public and private cluster nodes2.4.5. Control plane public vs. private endpoints2.5. Summary2.6. Exam questions3. Implementing Virtual Private Cloud (VPC) instances3.1. Configuring VPC resources3.1.1. Creating VPCs3.1.2. Creating subnets3.1.3. Listing subnets3.1.4. Listing VPCs3.1.5. Deleting VPCs3.2. Configuring VPC Network Peering3.3. Creating a Shared VPC network and sharing subnets with other projects3.3.1. Host and service project concepts3.3.2. Shared VPC deep dive3.3.3. Assigning roles to principals3.3.4. Creating the shared VPC3.3.5. Creating the service projects3.3.6. Enabling Compute API for service and host projects3.3.7. Enabling host project3.3.8. Attaching service projects3.3.9. Assigning individual subnet-level roles to service projects3.4. Using a Shared VPC3.4.1. Listing usable subnets3.4.2. Creating VMs3.4.3. Verifying VMs connectivity3.4.4. Deleting VMs3.5. Sharing subnets using folders3.6. Configuring API access to Google services (e.g., Private Google Access, public interfaces)3.6.1. Configuring Private Google Access (PGA)3.6.2. Configuring Private Service Connect (PSC)3.7. Expanding VPC subnet ranges after creation3.8. Configuring routing3.8.1. Static vs. dynamic routing3.8.2. Global vs. regional dynamic routing3.8.3. Routing policies using tags and priority3.8.4. Internal load balancer as a next hop3.8.5. Custom route import/export over VPC Network Peering3.9. Configuring and maintaining Google Kubernetes Engine clusters. Considerations include:3.9.1. VPC-native clusters using alias IPs3.9.2. Clusters with Shared VPC3.9.3. Creating Cluster Network Policies3.9.4. Private clusters and private control plane endpoints3.9.5. Adding authorized networks for cluster control plane endpoints3.10. Configuring and managing firewall rules. Considerations include:3.10.1. Target network tags and service accounts3.10.2. Rule priority3.10.3. Protocols and Ports3.10.4. Direction3.10.5. Firewall rule logs3.10.6. Summary4. Implementing VPC Service Controls4.1. Creating and configuring access levels and service perimeters4.2. Service perimeter deep dive4.3. VPC accessible services4.4. Perimeter bridges4.5. Audit logging4.6. Dry run mode4.7. Dry-run perimeter deep dive4.8. Exam questions5. Configuring load balancing5.1. Google Cloud load balancers family5.2. Backend services and network endpoint groups (NEGs)5.3. Firewall rules to allow traffic and health checks to backend services5.4. Health checks for backend services and target instance groups5.5. Configuring backends and backend services with balancing method (e.g., RPS, CPU, Custom), session affinity, and capacity scaling/scaler5.6. TCP and SSL proxy load balancers5.7. Load balancers (e.g., External TCP/UDP Network Load Balancing, Internal TCP/UDP Load Balancing, External HTTP(S) Load Balancing, Internal HTTP(S) Load Balancing)5.8. Protocol forwarding5.9. Accommodating workload increases using autoscaling vs. manual scaling5.10. Configuring Google Cloud Armor policies. Considerations include:5.11. Security policies5.12. Web application firewall (WAF) rules (e.g., SQL injection, cross-site scripting, remote file inclusion)5.13. Attaching security policies to load balancer backends5.14. Configuring Cloud CDN. Considerations include:5.15. Enabling and disabling5.16. Cloud CDN5.17. Cache keys5.18. Invalidating cached objects5.19. Signed URLs5.20. Custom origins6. Configuring advanced networking services6.1. Configuring and maintaining Cloud DNS6.1.1. Managing zones and records6.1.2. Migrating to Cloud DNS6.1.3. DNS Security Extensions (DNSSEC)6.1.4. Forwarding and DNS server policies6.1.5. Integrating on-premises DNS with Google Cloud6.1.6. Split-horizon DNS6.1.7. DNS peering6.1.8. Private DNS logging6.2. Configuring Cloud NAT6.2.1. Addressing6.2.2. Port allocations6.2.3. Customizing timeouts6.2.4. Logging and monitoring6.2.5. Restrictions per organization policy constraints6.3. Configuring network packet inspection6.3.1. Packet Mirroring in single and multi-VPC topologies6.3.2. Capturing relevant traffic using Packet Mirroring source and traffic filters6.3.3. Routing and inspecting inter-VPC traffic using multi-NIC VMs (e.g., next-generation firewall appliances)6.3.4. Configuring an internal load balancer as a next hop for highly available multi-NIC VM routing7. Implementing hybrid interconnectivity7.1. Configuring Cloud Interconnect7.1.1. Dedicated Interconnect connections and VLAN attachments7.1.2. Partner Interconnect connections and VLAN attachments7.2. Configuring a site-to-site IPsec VPN7.2.1. High availability VPN (dynamic routing)7.2.2. Classic VPN (e.g., route-based routing, policy-based routing)7.3. Configuring Cloud Router7.3.1. Border Gateway Protocol (BGP) attributes (e.g., ASN, route priority/MED, link-local addresses)7.3.2. Custom route advertisements via BGP7.3.3. Deploying reliable and redundant Cloud Routers8. Managing network operations8.1. Logging and monitoring with Google Cloud’s operations suite8.1.1. Reviewing logs for networking components (e.g., VPN, Cloud Router, VPC Service Controls)8.2. Monitoring networking components (e.g., VPN, Cloud Interconnect connections and interconnect attachments, Cloud Router, load balancers, Google Cloud Armor, Cloud NAT)8.3. Managing and maintaining security8.4. Firewalls (e.g., cloud-based, private)8.5. Diagnosing and resolving IAM issues (e.g., Shared VPC, security/network admin)8.6. Maintaining and troubleshooting connectivity issues8.6.1. Draining and redirecting traffic flows with HTTP(S) Load Balancing8.6.2. Monitoring ingress and egress traffic using VPC Flow Logs8.6.3. Monitoring firewall logs and Firewall Insights8.6.4. Managing and troubleshooting VPNs8.6.5. Troubleshooting Cloud Router BGP peering issues8.7. Monitoring, maintaining, and troubleshooting latency and traffic flow8.8. Testing network throughput and latency8.9. Diagnosing routing issues8.10. Using Network Intelligence Center to visualize topology, test connectivity, and monitor performance
Enhancing Adobe Acrobat Forms with JavaScript
Take your PDF forms to the next level! In this book, you’ll learn various ways to further improve your PDF forms using simple JavaScript coding. You’ll also discover how a few lines of code can speed up your workflow when working with multiple PDFs in Action Wizard.Enhancing Adobe Acrobat Forms with JavaScript covers up-to-date, real working examples that you can easily download and practice with and edit to suit your own projects. This book also shows workarounds and solutions to various form issues you might encounter. Feel empowered by it and improve your PDF documents!JavaScript has been a part of Adobe Acrobat for many versions. However, few people use its features and focus mainly on using basic form properties, never delving deeper into Acrobat’s full capabilities. While information on the web can be helpful, if you don’t know enough about how to use JavaScript in Acrobat you will be left with poor results. JavaScript can be difficult to learn, but it does not need to be scary. This book explains in simple steps for beginner to intermediate level so that you can take full advantage of Acrobat’s capabilities for your own projects.WHAT YOU WILL LEARN• Learn simplified field notation and basic JavaScript for Acrobat• Work with buttons that can be used for navigation• Improve form navigation and printing of forms• Add various types of alerts and custom validations to improve client-entered-data• Learn the basics of how to prepare a form for e-signingWHO IS THIS BOOK FORThis book is for anyone who needs to create forms for clients or websites. Students, lawyers, accountants, and human resources will be able to take their work to the next level by streamlining their workflow and utilizing advanced JavaScript features in Adobe Acrobat.Jennifer Harder has worked in the graphic design industry for over fifteen years. She has a degree in graphic communications and is currently teaching Acrobat, and Adobe Creative Cloud courses at Langara College. She is also author of several Apress books and related videos.Part 1: Basic Form ImprovementsChapter 1: A Fundamental Forms PrimerSub -Topics:• Forms Review• Fields Refresher• Properties Refreshero Text Box Field Properties and New Date Field Propertieso Dropdown Propertieso List Box Propertieso Check Box Propertieso Radio Button Propertieso Button Properties and Image Propertieso Digital Signature Propertieso Barcode Properties• Tab Properties Refresher• Setting Field Tab Order using the menu options• Clearing a Form while workingChapter 2: Introduction to ActionsSub – Topics:• Getting Started• Rating Forms Value Averaging and Sum: Working with Text Fieldso The Validate Tab• Page 2 of Project: The Calculate Tab for the Grand Total Using Sum• Sum and Averaging Using Check Boxes or Radio Buttons with Text Fieldso Using Radio Buttons on Page 3 of the Projecto Using Check Boxes on Page 3 of the Projecto Learning how check boxes can become radio buttons• Basic Action Button Triggers for Reset Buttons and Printing Buttonso Reset Buttono Print Form ButtonChapter 3: Creating a QR Code Custom StampSub - Topics:• Customizing Your QR Code Stamp• QR Code Creation• Using the Stamp Tool• Final Thoughts: QR Code for Professional PrintingChapter 4: Buttons, Navigation, Form and Non-Form ActionsSub - Topics:• Creating a Button Icono Example of a Button as a Label Only• Non-Form Properties Actionso Pageso Bookmarkso Web Hyperlinkso Rich Media Non-Form Navigation Buttonso Layers Basic Actionso Other Non-Form Actions• Triggers for Actions• Choose an Action That Requires No Code• Newsletter Navigation with Buttons• Form Navigation with a Button as Helpful Hint• Adding a Comb of Characters• Before Comb and After Comb• More Action Triggers to Show and Hideo Hide and Clear Fields Button• Set Layer Visibilityo Using Bookmarkso Using ButtonsPart 2: Simplified Field Notation and Basic JavaScriptChapter 5: Introduction to Simplified Field Notation and JavaScriptSub - Topics:• Getting Started• Text Field, Date, and Dropdown Menu Propertieso Action Tabo Format Tabo Validate Tabo Calculate Tabo Check Box, Radio Button, Image Field, and Button Propertieso List Box Propertieso Digital Signature Propertieso Barcode Propertieso Global Document JavaScripto Web Links and Referenceso Regular Forms vs. E-Sign Forms• JavaScript and Acrobat on the Document LevelChapter 6: Basic and Complex CalculationsSub - Topics:• Getting Started• Sum Value• Simplified Field Notation• JavaScript Custom Calculation Script• Resetting Your Field of Focus• Final Thoughtso The Final Line of Code (Setting the 0 value to blank)o Dropdown AlternativesChapter 7: Format CalculationsSub - Topics:• Number Formatting• Formatting with a Percentageo A Workaround for the Percentage• Date Formatting• Time Formatting• Final Thoughtso Dropdown AlternativesChapter 8: Various JavaScript Alerts, Notes and Time StampsSub - Topics:• Alert Types• Create a Document JavaScript• Viewer Version and Validation Alert• Document Actionso Document Will Closeo Document Will Print• Alerts Working with Buttons• Adding a Comment Note, Signature, and Time StampChapter 9: Create Help for Clients with Rollover Text and AlertsSub - Topics:• The Rollover Methodo Mouse Entero Mouse Exito Extra Non-Custom JavaScript Check Box Exampleo How to Show, Hide Fields with JavaScript• The Default Text Method• The Alert Methodo Customer’s Full Nameo Dateo Customer Order Codeo Customer’s Company Name• How to Duplicate Text for multiple fields and make fields read only with JavaScript• Final ThoughtsChapter 10: Various Types of Formatting with JavaScriptSub - Topics:• Adding Global Formatting to Text Fields• Color Properties• Multi-Line Buttons• Multi-Line Text• Complex Formatting Using Check Boxes and Text Fields• Rich Text Formatting for Text Fields and Comments• Silent Printing• Options for Submit Button using email• Final ThoughtsPart 3: Working with More Complex FormsChapter 11: Validation with Text Boxes, Alerts and Radio ButtonsSub - Topics:• Money Transfer Example• Changing the Shipping Price Using Radio Buttons• Additional Checkbox and Radio Button examples with JavaScript and Text Fields and how to change data.• Text Field Validation with Regular Expressionso Telephone Validationo Name Validationo Account Number Validationo Email and URL Validationo Another Phone and Date Example with Two Variables• Final ThoughtsChapter 12: Working with Dropdown MenusSub - Topics:• Current Skills Request Form• Parts Order Form• Final Thoughtso Load a Lengthy Single Dropdown or List MenuChapter 13: Working with List BoxesSub - Topics:• List Box Priority List with Control Buttonso The Add Buttono The Delete Buttono The Clear or Reset Buttono The Up Buttono The Down Button• Check Box, Dropdown, and List Box Example 1• Check Box, List Box, and Multi-Dropdown Example 2• Button Slide Show Variationo Extra Example Priority List Improved• Final Thoughtso Hidden Fieldso Using List Boxes for Number RatingChapter 14: Advanced Navigation: The Popup MenuSub – Topics:• The Popup Menu Example• Final ThoughtsPart 4: Beyond the BasicsChapter 15: Action Wizard and JavaScriptSub – Topics:• Working with Action Wizardo Reuse JavaScript from Chapter 8• Is It a Custom Action or a Custom Command?o Create and Manage Custom CommandsChapter 16: Multi-State Check BoxesSub - Topics:• The Problem of Multi-State Check Boxes• Bonus Star Rating Idea• Select All or Deselect All Check Boxes at OnceChapter 17: Importing an Image into a ButtonSub - Topics:• Creating the ButtonChapter 18: Multiple FormattingSub - Topics:• The Problem of Multiple Formatting• Option 1: Do It Yourselfo Price Scripto No Price Scripto Adding a Degree Symbol and Formatting range• Option 2: Call a ProfessionalChapter 19: Digital Signatures and BarcodesSub - Topics:• Digital Signatures and Security• BarcodesChapter 20: What are E-Signature Forms and Web Forms?Sub - Topics:• A brief Look at E- Signatures and Resources• What are Web Forms, do they have JavaScript? and related ResourcesPart 5: Putting It into PracticeChapter 21: Homework AssignmentsSub - Topics:• Homework Assignment 1: Show and Hide• Homework Assignment 2: Working with JavaScript to Create Formulaso Area of a Circle (A = π r 2 )o Field: CircumferenceRow1 Circumference of a Circle (C = 2 π r )o Field: VolumeRow1 Volume of a Sphere (V = 4/3 π r3 )o Field: FahrenheitRow1 Celsius to Fahrenheit to Formula. (°C x 9/5) + 32 = °F.o Field: CelsiusRow1_2 Fahrenheit to Celsius Formula. (°F - 32) x 5/9 = °C• Homework Assignment 3: Custom Validation and Regular Expressions• Homework Assignment 4: Personal Dropdown Menu and Definitions Text Box
Introduction to Prescriptive AI
Gain a working knowledge of prescriptive AI, its history, and its current and future trends. This book will help you evaluate different AI-driven predictive analytics techniques and help you incorporate decision intelligence into your business workflow through real-world examples.The book kicks off with an introduction to decision intelligence and provides insight into prescriptive AI and how it can be woven into various business strategies and frameworks. You'll then be introduced to different decision intelligence methodologies and how to implement them, along with advantages and limitations of each. Digging deeper, the authors then walk you through how to perform simulations and interpret the results. A full chapter is devoted to embedding decision intelligence processes and outcomes into your business workflow using various applications. The book concludes by exploring different cognitive biases humans are prone to, and how those biases can be eliminated by combining machine and human intelligence.Upon completing this book, you will understand prescriptive AI, tools, and techniques and will be ready to incorporate them into your business workflow.WHAT YOU WILL LEARN* Implement full-fledged decision intelligence applications using Python* Leverage the tools, techniques, and methodologies for prescriptive AI* Understand how prescriptive AI can be used in different domains through practical examples* Interpret results and integrate them into your decision makingWHO THIS BOOK IS FORData Scientists and Machine Learning Engineers, as well as business professionals who want to understand how AI-driven decision intelligence can help grow their business.AKSHAY R. KULKARNI is an artificial intelligence (AI) and machine learning (ML) evangelist and a thought leader. He has consulted several Fortune 500 and global enterprises to drive AI and data science–led strategic transformations. He is a Google developer, an author, and a regular speaker at major AI and data science conferences (including the O’Reilly Strata Data & AI Conference and Great International Developer Summit (GIDS)) . He is a visiting faculty member at some of the top graduate institutes in India. In 2019, he was featured as one of India’s “top 40 under 40” data scientists. In his spare time, Akshay enjoys reading, writing, coding, and helping aspiring data scientists. He lives in Bangalore with his family.ADARSHA SHIVANANDA is a data science and MLOps leader. He is working on creating world-class MLOps capabilities to ensure continuous value delivery from AI. He aims to build a pool of exceptional data scientists within and outside organizations to solve problems through training programs. He always wants to stay ahead of the curve. Adarsha has worked extensively in the pharma, healthcare, CPG, retail, and marketing domains. He lives in Bangalore and loves to read and teach data science.AVINASH MANURE is a seasoned Machine Learning Professional with 10+ years of experience building, deploying, and maintaining state-of-the-art machine learning solutions across different industries. He has 6+ years of experience leading and mentoring high-performance teams in developing ML systems catering to different business requirements. He is proficient in deploying complex machine learning and statistical modeling algorithms/techniques for identifying patterns and extracting valuable insights for key stakeholders and organizational leadership.Chapter 1: Decision Intelligence Overview.- Chapter 2: Decision Intelligence Requirements.- Chapter 3: Decision Intelligence Methodologies.- Chapter 4: Interpreting Results from Different Methodologies.- Chapter 5: Augmenting Decision Intelligence Results into the Business Workflow.- Chapter 6: Actions, Biases and Human-in-the-Loop.- Chapter 7: Case Studies.
Angewandte Data Science
Die Anwendungen der Disziplin Data Science erweitern und wandeln sich stetig. In diesem Buch geben Insider aus Praxis, Wissenschaft und Lehre detailliert die Ergebnisse ihrer Data-Science-Projekte, Methodenwissen sowie Knowhow zu Vorgehensweisen und Prozessmodellen an den Leser weiter. Dabei wird ein weit gespannter Querschnitt an konkreten Anwendungen beschrieben, erklärt und illustriert: von der Nutzung generativer KI-Systeme über quantitative Textanalyse, Predictive Policing, Erklärbarkeit von Machine-Learning-Modellen, experimentelle Datenanalyse in der Spektroskopie bis hin zu Datenvisualisierung, Strukturgleichungsmodellen und Varianzanalyse.Das Buch richtet sich an jeden, der sowohl am konkreten Einsatz von Datenwissenschaft, Statistik, Maschinellem Lernen und Künstlicher Intelligenz als auch am zugehörigen theoretischen Hintergrund interessiert ist. Praktikern, Studierenden und Lehrenden dürfte es von besonderem Nutzen sein: eine Vielzahl an Abbildungen, Diagrammen und Illustrationen ergänzen die reichhaltigen Textinformationen; Links zu Webseiten und Webapplikationen verweisen auf online verfügbare weitere Informationsquellen und Data-Science-Werkzeuge.LOTHAR B. BLUM lehrt als Hochschuldozent interaktives Informationsdesign, Datenvisualisierung und Advanced Analytics. Er ist Principal UX Designer beim Cloudsoftwareunternehmen Infor sowie Co-Founder und Organisator der Data Science Darmstadt Meetups.Einflüsse der Corona-Pandemie auf die deutsche Presse-Sprache.- Predictive Policing.- Am Anfang war der Prompt.- Erklärbarkeit als Schlüssel für den verantwortungsvollen Umgang mit KI. - Strukturgleichungsmodelle versus Varianzanalyse.- Was ist schon normal in diesen Zeiten? - Sankey-Diagramm reloaded.- Jenseits der Algorithmen.- A Scalable Architecture for Smart Genomic Data Analysis in Medical Laboratories.- Die Sieben V der Daten.– Scope Creep, GUI, Skalierung.
Pro Cryptography and Cryptanalysis with C++23
Develop strong skills for writing cryptographic algorithms and security schemes/modules using C++23 and its new features. This book will teach you the right methods for writing advanced cryptographic algorithms, such as elliptic curve cryptography algorithms, lattice-based cryptography, searchable encryption, and homomorphic encryption. You'll also examine internal cryptographic mechanisms and discover common ways in which the algorithms can be implemented and used correctly in practice.The authors explain the mathematical basis of cryptographic algorithms in terms that a programmer can easily understand. They also show how “bad” cryptography can creep in during implementation and what “good” cryptography should look like by comparing advantages and disadvantages based on processing time, execution time, and reliability.WHAT YOU WILL LEARN* Discover what modern cryptographic algorithms and methods are used for * Design and implement advanced cryptographic mechanisms * See how C++23 and its new features are impact the implementation of cryptographic algorithms* Practice the basics of public key cryptography, including ECDSA signatures and more* See how most of the algorithms can be brokenWHO THIS BOOK IS FORProfessional programmers, developers, and software engineers who are developing cryptography algorithms and security schemes/modules in C++. Prior C++ programming and IDE experience and some basic experience of cryptography concepts (symmetric and asymmetric) highly recommended.MARIUS IULIAN MIHAILESCU, PHD is CEO at Dapyx Solution Ltd., a company based in Bucharest, Romania and involved in information security- and cryptography-related research projects. He is a lead guest editor for applied cryptography journals and a reviewer for multiple publications with information security and cryptography profiles. He authored and co-authored more than 30 articles in conference proceedings, 25 articles in journals, and three books. For more than six years he has served as a lecturer at well-known national and international universities (University of Bucharest, “Titu Maiorescu” University, Kadir Has University in, Istanbul, Turkey). He has taught courses on programming languages (C#, Java, C++, Haskell), and object-oriented system analysis and design with UML, graphs, databases, cryptography and information security. He served for three years as IT officer at Royal Caribbean Cruises Ltd. where he dealt with IT infrastructure, data security, and satellite communications systems. He received his PhD in 2014 and his thesis was on applied cryptography over biometrics data. He holds two MSc in information security and software engineering.STEFANIA LOREDANA NITA, PHD is a software developer at the Institute of Computer Science of the Romanian Academy and a PhD with her thesis on advanced cryptographic schemes using searchable encryption and homomorphic encryption. She has served more than two years as an assistant lecturer at the University of Bucharest where she taught courses on subjects such as advanced programming techniques, simulation methods, and operating systems. She has authored and co-authored more than 15 workpapers at conferences and journals, and has authored two books on he Haskell programming language. She is a lead guest editor for special issues on information security and cryptography such as Advanced Cryptography and Its Future: Searchable and Homomorphic Encryption. She holds an MSc in software engineering and two BSc in computer science and mathematics.Part I: Foundations1: Introduction2: Cryptography Fundamentals3: Mathematical Background and Its Applicability4: Large Integer Arithmetic5: Floating Point Arithmetic6: New Features in C++237: Secure Coding Guidelines8: Cryptography Libraries in C/C++23Part II: Pro Cryptography9: Elliptic Curve Cryptography10: Lattice-based Cryptography11: earchable Encryption12: Homomorphic Encryption13: (Ring) Learning with Errors Cryptography14: Chaos-based Cryptography15: Big Data Cryptography16:Cloud Computing CryptographyPart III: Pro Cryptanalysis17: Getting Started with Cryptanalysis18: Cryptanalysis Attacks and Techniques19: Linear and Differential Cryptanalysis20: Integral Cryptanalysis21: Brute Force and Buffer Overflow Attacks22: Text Characterization23: Implementation and Practical Approach of Cryptanalysis Methods
How to Catch a Phish
Learn how to detect, analyze, and respond to phishing emails, the top infection vector used by cybercriminals. The repeatable process described in this book has been cultivated and tested in real-life incidents and validated across multiple threat landscapes and environments.Every organization and individual with an email account is susceptible to deceptive emails sent by attackers with nefarious intentions. This activity, known as phishing, involves an attacker attempting to lure individuals into providing sensitive information or performing a predetermined action. Attacks vary in sophistication, but the core skills and process to detect, analyze, and respond to a suspicious message does not change.Attackers have preyed on victims with convincing and not-so-convincing phishing emails to gain initial footholds into networks around the world for over 30 years. This attack method has been rapidly growing in popularity and continues to be the number one method that organizations and individuals struggle to defend against. Regardless of what any vendor or organization will tell you, no infallible tool exists to eliminate this threat completely.This book teaches you how to analyze suspicious messages using free tools and resources. You will understand the basics of email, tactics used by attackers, and a repeatable process to systematically analyze messages and respond to suspicious activity.YOU WILL LEARN HOW TO:* Safely save email messages as attachments for analysis* Identify what information is in an email header* Review header information and extract key indicators or patterns used for detection* Identify signs of a suspicious or malicious email message* Detect the tactics that attackers use in phishing emails* Safely examine email links and attachments* Use a variety of free and simple tools to analyze email messagesWHO THIS BOOK IS FORCybersecurity professionals and interested computer security enthusiasts currently holding or aspiring to obtain positions such as IT Security Analyst, Network Defender, Security Operations Center Analyst, or Help Desk Technician. Readers should have a general understanding of how email works and some ways that attackers use this platform for initial access.Nick Oles is a cybersecurity expert with over 15 years of operational experience in military, industry, and academic environments. He has worked on incident response and threat hunting teams and consulted with Fortune 150 organizations, small businesses, and US Department of Defense entities. Nick has served his country for over a decade in the cyber and special operations communities, earning multiple military accolades, completing worldwide deployments, and serving in joint special operations environments. He has advised award-winning academic centers on cyber-program development and management, as well as created and taught academic and certification courses on a variety of cybersecurity topics. Nick has detected, analyzed, and responded to thousands of security incidents over his career. He continues to actively contribute to the cybersecurity community and teach students at all skill levels while still serving his country.CHAPTER 1. HOW EMAIL WORKS1.1 Understanding Email Architecture1.2 Basic Components of an email message1.2.1 Email Header1.2.2 Email ContentCHAPTER 2. PHISHING TACTICS AND TECHNIQUES2.1 How phishers get you to click2.1.1 Elicitation and enticement2.1.2 Key indicators of suspicious messagesCHAPTER 3. PICERL PROCESS EXPLAINED3.1 Preparation3.2 Identification3.3 Containment3.4 Eradication3.5 Remediation3.6 Lessons LearnedCHAPTER 4. ANALYZING MESSAGE CONTENTCHAPTER 5. EMBEDDED LINK ANALYSIS5.1 Process safely extract and find links5.2 Tools to submit links for analysisCHAPTER 6. ATTACHMENT ANALYSIS6.1 How to handle attachments6.2 Tools used to analyze attachmentsCHAPTER 7. LOG SEARCHING AND RESPONSE7.1 Key logs records to search7.2 Response verbiage and communicationCHAPTER 8. MITIGATION AND LESSONS LEARNED
The Active Defender
IMMERSE YOURSELF IN THE OFFENSIVE SECURITY MINDSET TO BETTER DEFEND AGAINST ATTACKSIn The Active Defender: Immersion in the Offensive Security Mindset, Senior Information Security Forensic Analyst Dr. Catherine J. Ullman delivers an expert treatment of the Active Defender approach to information security. In the book, you’ll learn to understand and embrace the knowledge you can gain from the offensive security community. You’ll become familiar with the hacker mindset, which allows you to gain emergent insight into how attackers operate and better grasp the nature of the risks and threats in your environment. The author immerses you in the hacker mindset and the offensive security culture to better prepare you to defend against threats of all kinds. You’ll also find:* Explanations of what an Active Defender is and how that differs from traditional defense models* Reasons why thinking like a hacker makes you a better defender* Ways to begin your journey as an Active Defender and leverage the hacker mindsetAn insightful and original book representing a new and effective approach to cybersecurity, The Active Defender will be of significant benefit to information security professionals, system administrators, network administrators, and other tech professionals with an interest or stake in their organization’s information security. CATHERINE J. ULLMAN is a security researcher, speaker, and Principal Technology Architect, Security at the University at Buffalo. She is a DFIR specialist and expert in incident management, intrusion detection, investigative services, and personnel case resolution. She offers security awareness training in an academic setting and is a well-known presenter at information security conferences, including DEF CON and Blue Team Con.
Künstliche Intelligenz und Data Science in Theorie und Praxis
Dieser Sammelband verbindet theoretische Grundlagen und praktische Anwendungen von Künstlicher Intelligenz (KI) und Data Science: Anerkannte Experten stellen in ihren Beiträgen den aktuellen Stand in Forschung und Wirtschaft dar – und bieten so einen einzigartigen Überblick über aktuelle Konzepte und ihre Umsetzung in Unternehmen.Im ersten Teil des Buchs werden die Methoden und Algorithmen skizziert, die sich größtenteils aus einer Kombination von Statistik und Informatik ergeben und auf Verfahren des Maschinellen Lernens bis hin zu Deep Learning und KI basieren. Im zweiten Teil wird die konzeptionelle Umsetzung in der Praxis skizziert: Hier wird insbesondere aufgezeigt, welche Herausforderungen in der Praxis auftreten – ob nun bei der Einbettung der Daten-Use-Cases in eine Gesamtstrategie oder bei der Produktivsetzung, Weiterentwicklung und dem Betrieb von Daten-basierten Lösungen. Der dritte Teil zeigt das breite Potpourri von Data Science in der Praxis: Branchengrößenwie Allianz, ADAC, BMW, Deutsche Bahn, Lufthansa, REWE, RTL, St. Galler Stadtwerke, SwissRe und viele weitere zeigen konkret, welche Erfahrungen sie bei ihren Projekten gesammelt haben. Fachartikel von über 20 namhaften Unternehmen decken die spezifischen Anforderungen ihrer jeweiligen Branchen ab.Das Buch möchte die interdisziplinäre Diskussion und Kooperation zwischen Wissenschaft und Wirtschaft fördern und richtet sich daher an verschiedene Lesergruppen:* Studierende und Absolventen, die Orientierung für die eigene Laufbahn suchen.* Forschende und Lehrende, die einen Einblick in praxisrelevante Einsatzgebiete erhalten möchten.* Anwender, Praktiker und Entscheider, die sich über Chancen und Herausforderungen von KI in der Praxis informieren möchten.ANDREAS GILLHUBER ist Co-CEO bei der Alexander Thamm GmbH, einer führenden Beratung für Data Science, KI und ML im deutschsprachigen Raum.GÖRAN KAUERMANN ist Universitätsprofessor an der Ludwigs-Maximilians-Universität München und hat dort den Elite-Studiengang Data Science eingerichtet.WOLFGANG HAUNER ist als Leiter Group Data Analytics der Allianz SE global verantwortlich für Daten- und Analytics-Lösungen für die Allianz Unternehmensgruppe.Vorwort.- Grundlagen von Data Science.- Data Science in der Praxis.- Beispiele aus der Praxis-Ausblick/Wohin geht die Reise.
Data Wrangling
DATA WRANGLINGWRITTEN AND EDITED BY SOME OF THE WORLD’S TOP EXPERTS IN THE FIELD, THIS EXCITING NEW VOLUME PROVIDES STATE-OF-THE-ART RESEARCH AND LATEST TECHNOLOGICAL BREAKTHROUGHS IN DATA WRANGLING, ITS THEORETICAL CONCEPTS, PRACTICAL APPLICATIONS, AND TOOLS FOR SOLVING EVERYDAY PROBLEMS.Data wrangling is the process of cleaning and unifying messy and complex data sets for easy access and analysis. This process typically includes manually converting and mapping data from one raw form into another format to allow for more convenient consumption and organization of the data. Data wrangling is increasingly ubiquitous at today’s top firms. Data cleaning focuses on removing inaccurate data from your data set whereas data wrangling focuses on transforming the data’s format, typically by converting “raw” data into another format more suitable for use. Data wrangling is a necessary component of any business. Data wrangling solutions are specifically designed and architected to handle diverse, complex data at any scale, including many applications, such as Datameer, Infogix, Paxata, Talend, Tamr, TMMData, and Trifacta. This book synthesizes the processes of data wrangling into a comprehensive overview, with a strong focus on recent and rapidly evolving agile analytic processes in data-driven enterprises, for businesses and other enterprises to use to find solutions for their everyday problems and practical applications. Whether for the veteran engineer, scientist, or other industry professional, this book is a must have for any library. M. NIRANJANAMURTHY, PhD, is an assistant professor in the Department of Computer Applications, M S Ramaiah Institute of Technology, Bangalore, Karnataka. He earned his PhD in computer science at JJTU, Rajasthan, India. He has over 11 years of teaching experience and two years of industry experience as a software engineer. He has published several books, and he is working on numerous books for Scrivener Publishing. He has published over 60 papers for scholarly journals and conferences, and he is working as a reviewer in 22 scientific journals. He also has numerous awards to his credit. Kavita Sheoran, PhD, is an associate professor in the Computer Science Department, MSIT, Delhi, and she earned her PhD in computer science from Gautam Buddha University, Greater Noida. With over 17 years of teaching experience, she has published various papers in reputed journals and has published two books. GEETIKA DHAND, PhD, is an associate professor in the Department of Computer Science and Engineering at Maharaja Surajmal Institute of Technology. After earning her PhD in computer science from Manav Rachna International Institute of Research and Studies, Faridabad, she has taught for over 17 years. She has published one book and a number of papers in technical journals. PRABHJOT KAUR has over 19 years of teaching experience and has earned two PhDs for her work in two different research areas. She has authored two books and more than 40 research papers in reputed journals and conferences. She also has one patent to her credit.
Predicting the Unknown
As a society, we’re in a constant struggle to control uncertainty and predict the unknown. Quite often, we think of scientific fields and theories as being separate from each other. But a more careful investigation can uncover the common thread that ties many of those together. From ChatGPT, to Amazon’s Alexa, to Apple’s Siri, data science, and computer science have become part of our lives. In the meantime, the demand for data scientists has grown, as the field has been increasingly called the “sexiest profession.”This book attempts to specifically cover this gap in literature between data science, machine learning and artificial intelligence (AI). How was uncertainty approached historically, and how has it evolved since? What schools of thought exist in philosophy, mathematics, and engineering, and what role did they play in the development of data science? It uses the history of data science as a stepping stone to explain what the future might hold.Predicting the Unknown provides the framework that will help you understand where AI is headed, and how to best prepare for the world that’s coming in the next few years, both as a society and within a business. It is not technical and avoids equations or technical explanations, yet is written for the intellectually curious reader, and the technical expert interested in the historical details that can help contextualize how we got here.WHAT YOU’LL LEARN* Explore the bigger picture of data science and see how to best anticipate future changes in that field* Understand machine learning, AI, and data science* Examine data science and AI through engaging historical and human-centric narratives WHO IS THIS BOOK FORBusiness leaders and technology enthusiasts who are trying to understand how to think about data science and AIDr. Stylianos (Stelios) Kampakis is a data scientist, data science educator and blockchain expert with more than 10 years of experience. He has worked with decision makers from companies of all sizes: from startups to organizations like the US Navy, Vodafone ad British Land. His work expands multiple sectors including fintech (fraud detection and valuation models), sports analytics, health-tech, general AI, medical statistics, predictive maintenance and others. He has worked with many different types of technologies, from statistical models, to deep learning to blockchain and he has two patents pending to his name. He has also helped many people follow a career in data science and technology.He is a member of the Royal Statistical Society, honorary research fellow at the UCL Centre for Blockchain Technologies, a data science advisor for London Business School, and CEO of The Tesseract Academy and tokenomics auditor at Hacken. As a well-known data-science educator, he has published two books, both of them getting 5 stars on Amazon. His personal website gets more than 10k visitors per month, and he is also a data science influencer on LinkedIn.PREFACEAuthor’s note to the curious readerPROLOGUECHAPTER ONE – WHERE ARE WE NOW? A BRIEF HISTORY OF UNCERTAINTYNot all uncertainty is created equalCHAPTER TWO - TRUTH, LOGIC AND THE PROBLEM OF INDUCTIONThe first black swanCHAPTER THREE - SWANS AND SPACE INVADERSOccam’s razor, space invaders and lizard peopleCHAPTER FOUR - PROBABILITY: TO BAYES, OR NOT TO BAYES?Frequentist or Bayesian?The formulation of Bayes’ theoremAfter LaplaceCHAPTER FIVE - WHAT’S MATHS GOT TO DO WITH IT? THE POWER OF PROBABILITY DISTRIBUTIONSOther Distribution ModelsIssues with this view of uncertaintyBounds and limitsCHAPTER SIX - ALTERNATIVE IDEAS: FUZZY LOGIC AND INFORMATION THEORYInformation Theory – Measuring UncertaintyCHAPTER SEVEN – STATISTICS: THE OLDEST KID ON THE BLOCKDescriptive vs Inferential StatisticsHypothesis Testing: Significant or Not?What the p?Statistical modelling: A useful abstractionCHAPTER EIGHT - MACHINE LEARNING: INSIDE THE BLACK BOXData Science and History of Machine LearningChoose Your Learning Type: Supervised, Unsupervised, Reinforcement, or Other?The Bias-Variance Trade-OffMachine Learning vs Statistics: Why the ‘Dumb’ Approach WorksMachine Learning ShortcomingsCHAPTER NINE - CAUSALITY: UNDERSTANDING THE ‘WHY’How to Approach Causality?Causality in our MindCHAPTER TEN - FORECASTING, AND PREDICTING THE FUTURE: THE FOX AND THE TRUMPA brief history of forecastingForecasting in practice: Newton and the madness of men, Trump, Brexit, and losing money through mathematical modellingHow to do forecasting: A story of foxes and hedgehogsCHAPTER ELEVEN - THE LIMITS OF PREDICTION (PART A): A FUTILE PURSUIT?Learning theory: what can we know about what we don’t know?Monte Carlo Simulations: What Does a Casino Have to do with Science?CHAPTER TWELVE - THE LIMITS OF PREDICTION (PART B): GAME THEORY, AGENT-BASED MODELLING AND COMPLEXITY (ACTIONS AND REACTIONS)Agent-based Modelling: Crafting artificial WorldsComplexity Theory: Simulation vs the Limits of PredictionStudying Complexity is a Complex EndeavourLearning from Complexity: The Limits of Computation are the Limits of UncertaintyCHAPTER THIRTEEN - UNCERTAINTY IN US: HOW THE HUMAN MIND HANDLES UNCERTAINTYUncertainty and our MindUncertainty and our BrainCHAPTER FOURTEEN - BLOCKCHAIN: UNCERTAINTY IN TRANSACTIONSThe Internet of TrustHow Blockchain WorksFrom Crypto-Anarchism to Drug Trafficking: The unconventional Beginnings of an interesting TechnologyI Can’t Trust you, but I Can Trust the BlockchainCHAPTER FIFTEEN - ECONOMIES OF PREDICTION: A NEW INDUSTRIAL REVOLUTIONUncertainty brokersIndustries of incomplete InformationPrediction Industries and AutomationThe global Economy against UncertaintyEPILOGUE: THE CERTAINTY OF UNCERTAINTY
Understand, Manage, and Measure Cyber Risk
When it comes to managing cybersecurity in an organization, most organizations tussle with basic foundational components. This practitioner’s guide lays down those foundational components, with real client examples and pitfalls to avoid.A plethora of cybersecurity management resources are available—many with sound advice, management approaches, and technical solutions—but few with one common theme that pulls together management and technology, with a focus on executive oversight. Author Ryan Leirvik helps solve these common problems by providing a clear, easy-to-understand, and easy-to-deploy "playbook" for a cyber risk management approach applicable to your entire organization.This second edition provides tools and methods in a straight-forward, practical manner to guide the management of a cybersecurity program. Expanded sections include the critical integration of cyber risk management into enterprise risk management, the important connection between a Software Bill of Materials and Third-party Risk Programs, and additional "how to" tools and material for mapping frameworks to controls.PRAISE FOR UNDERSTAND, MANAGE, AND MEASURE CYBER RISKWhat lies ahead of you in the pages of this book? Clean practicality, not something that just looks good on paper—brittle and impractical when exposed to the real world. I prize flexibility and simplicity instead of attempting to have answers for everything and the rigidity that results. This simplicity is what I find valuable within Ryan's book. TIM COLLYER, MOTOROLA SOLUTIONSIt seems that I have found a kindred spirit—a builder who has worked with a wide variety of client CISOs on their programs, gaining a deep understanding of how a successful and sustainable program should be constructed. Ryan's cyber work in the US Department of Defense, his McKinsey & Company consulting, and his advisory and survey work with IANS give him a unique global view of our shared passion. NICHOLAS J. MANKOVICH, PHD, MS, CISPPWHO THIS BOOK IS FORCISOs, CROs, CIOs, directors of risk management, and anyone struggling to pull together frameworks or basic metrics to quantify uncertainty and address riskRYAN LEIRVIK is a cybersecurity professional who has spent the better part of two decades enhancing information security programs at the world's largest institutions. With considerable US government and commercial sector experience, Ryan has employed his professional passion for cybersecurity at almost every level within an organization.A frequent speaker on the topic of information security, Ryan fields several questions on “How do I make sure I have a sustainable cyber program?” This book was written to help answer that question.Ryan has been the CEO of a cybersecurity research and development company, Chief of Staff and Associate Director of Cyber for the US Department of Defense, and a cybersecurity strategy consultant with McKinsey & Company. Ryan’s technology career started at IBM, and he has a master of IT degree from Virginia Tech, an MBA from Case Western Reserve University, as well as a bachelor of science from Purdue University. Ryan is also on the faculty at IANS.INTRODUCTIONPART 1: THE PROBLEMCHAPTER 1: THE SITUATIONCHAPTER 2: THE COMPLICATIONInformation Technology or “IT” became pervasive near 1995, and after a quarter-century of IT in organizations, managers, engineers, and board-level oversight still speak different languages. The language divide creates a disconnect in the strategy-to-management-to-tactical thread that is critical for overall organizational risk management, not to mention overall business management. This complicates the ability for these functions to align on one language for managing cyber risk.CHAPTER 3: THE RESOLUTIONOne unified approach to cybersecurity:· Be clear on identifying the risk· Understand the risk· Categorize the critical data at risk· Determine the causes, consequences, and accountability of a data breach· Identify the business impact of a breach· Simplify how you manage the risk· Apply a framework· Structure the organization (i.e., staff and management)· Prepare to respond (... and recover)· Build feedback mechanisms to measure the risk· Choose risk-informative metrics, Key Performance Indicators (KPI’s), and Key Risk Indicators (KPI’s· Apply appropriate resources (e.g., measuring projects, overseeing initiatives)PART 2: THE SOLUTIONCHAPTER 4: UNDERSTAND THE PROBLEMKnowing what “problem” you are solving is the most critical part of problem solving. It is important to spend time exploring the main issue. This typically means asking others what they see as the problem, gathering facts and opinions (and knowing the difference between them), and then establishing a recommended problem to solve that categorically encompasses all the facts you have gathered. For example, the audit team will likely talk about the problem of fines and resources to remain in compliance. The contracts team will likely talk about the risks brought about by outside companies (aka Third Parties), and the tech teams will likely talk about the immediate risks to the network, applications, or endpoints. Each team is looking at their part of the enterprise risk, but are they all looking to one specific problem that aligns them all? Typically not. So, the solution becomes the one problem everyone is solving for and helps them focus on that. In this case, that might be: critical data and systems at risk. Communicating as one problem everyone is solving for has the benefit of pulling everyone together, instead of trying to manage everyone from within their view of the problem -- risk to critical data or systems. The solution here is to get them all focused on one problem so that managing the problem is much easier -- with everyone understanding that the problem is (i.e., keeping critical data and systems secure), the management of that becomes an easier tactical activity.CHAPTER 5: MANAGE THE PROBLEM· Guidelines up front: Settle on one approach (i.e., Framework) that best fits the business· Complication is that no one framework fits any one organization’s risk profile perfectly· Key is to pick a framework as a starting point and modify it to the organization (and as cyber risk management matures)· Key to resolving this is to assign roles (e.g., an adversary, a manager, a third party); remember, there is a person at the center of the problem you are trying to manageCHAPTER 6: MEASURE THE PROBLEM· Guidelines up front: Board-level metrics are strategic, supported by tactical measures.· Objective is to communicate three things: (1) Understand what is at risk; (2) Manage that risk; and (3) Measure your management through feedback metrics· Educate the Board on what you are doing to reduce the risk· Communicate the value of your programs: provide insightful measures· Mature measures: measure what you can measure now, with a focus on what you want to measureCHAPTER 7: CONCLUSION* BE CLEAR ON IDENTIFYING THE RISK· Understand the risk· Categorize the critical data at risk· Determine the causes, consequences, and accountability of a data breach· Identify the business impact of a breach* SIMPLIFY HOW YOU MANAGE THE RISK · Apply a framework· Structure the organization (i.e., staff and management)· Prepare to respond (... and recover)* BUILD FEEDBACK MECHANISMS TO MEASURE THE RISK· Choose risk-informative metrics, Key Performance Indicators (KPI’s), and Key Risk Indicators (KPI’s· Apply appropriate resources (e.g., measuring projects, overseeing initiatives)APPENDIX: COMMON QUESTIONS (TBD)APPENDIX: ILLUSTRATIONS (TBD)
Beginning Microsoft Dataverse
Understand the role that Dataverse plays in the low-code revolution that helps businesses gain advantage from being more agile with technology. This book shows you how to use Dataverse to solve business problems by describing the layers of a solution in the Power Platform and the options that exist at each layer so you can make informed decisions as you develop your solutions. The book shows how Dataverse is a central piece of the Microsoft Power Platform and helps tech-savvy professionals move nimbly and seize the day when opportunities present themselves.The book starts out by covering the platform in terms of its layers so you can orient yourself with the features that exist at each level and what that means to you as a developer. You will learn how to work inside the data layer to design tables to store data and relationships and manage how it all works together. You will learn how to apply business logic and validation in the business layer to ensure data integrity and enforce process compliance. You will learn how to design interfaces in the presentation layer to allow users to interact with your data and processes in user-friendly applications. And you will learn how to utilize third-party integration tools to create seamless connections between your solution and legacy systems so you can develop enterprise-grade tools in record time.WHAT YOU WILL LEARN* Understand the layers of Dataverse and the features at each layer* Create tables and relationships to store data and manage interactions* Build applications to allow users to interact with your data using logical interfaces* Design business logic and workflows to ensure data integrity and automation* Configure security to control access to data and prevent unauthorized access* Explore the options for integration with third-party systems WHO THIS BOOK IS FORMicrosoft Power Platform users who want to learn how to access the power of the Power Platform and leverage Dataverse to build powerful, robust, and resilient tools; power users and citizen developers who are looking for tools to quickly build scalable business solutions that don’t require a strong developer background; pro developers who want to learn how to utilize use the Power Platform to speed up the development cycle and deliver value to customers faster than ever beforeBRIAN HODEL is a Microsoft Power Platform developer who is passionate about solving problems. His background in Lean Six Sigma and interest in application development converged as he began using what would eventually come to be known as the Power Platform. Since then, he has been developing enterprise solutions based on Dataverse in the Power Platform, speaking at conferences, participating on Customer Advisory Boards with Microsoft product development teams, and leading the internal Power Champions group at his current company. 1. Microsoft Power Platform2. Planning Your Solution Design3. Data Layer4. Business Logic Layer5. Presentation Layer6. Security7. Integration with Third-Party Tools8. Dataverse for Teams
Software im Automobil
Dieses Fach- und Lehrbuch enthält die maschinengenerierten Zusammenfassungen einer Datenbankrecherche zum Thema „Software im Automobil“. Die Vorgabe der Stichworte, die Struktur und die Selektion der Inhalte wurde vom Autor vorgenommen. Darüber hinaus hat der Autor die enthaltenen Artikel durch Einleitungen und Bewertungen in einen übergreifenden Zusammenhang gebracht und kommentiert. Auf diese Weise ist ein Werk entstanden, das Studierenden sowie Berufseinsteigern einen breiten Überblick über das fachliche Feld sowie Hinweise zur weiterführenden Literatur gibt und auf die weitere Arbeit in diesem Bereich vorbereitet. Fahrzeugarchitektur und Infrastruktur.- Software-basierte Funktionen.- Strukturierte Softwareentwicklung.- Software-Tests.- Reifegrad der Softwareentwicklung.
Functional Programming in R 4
Master functions and discover how to write functional programs in R. In this book, updated for R 4, you'll learn to make your functions pure by avoiding side effects, write functions that manipulate other functions, and construct complex functions using simpler functions as building blocks.In Functional Programming in R 4, you’ll see how to replace loops, which can have side-effects, with recursive functions that can more easily avoid them. In addition, the book covers why you shouldn't use recursion when loops are more efficient and how you can get the best of both worlds.Functional programming is a style of programming, like object-oriented programming, but one that focuses on data transformations and calculations rather than objects and state. Where in object-oriented programming you model your programs by describing which states an object can be in and how methods will reveal or modify that state, in functional programming you model programs by describing how functions translate input data to output data. Functions themselves are considered to be data you can manipulate and much of the strength of functional programming comes from manipulating functions; that is, building more complex functions by combining simpler functions.WHAT YOU'LL LEARN* Write functions in R 4, including infix operators and replacement functions* Create higher order functions* Pass functions to other functions and start using functions as data you can manipulate* Use Filer, Map and Reduce functions to express the intent behind code clearly and safely* Build new functions from existing functions without necessarily writing any new functions, using point-free programming* Create functions that carry data along with themWHO THIS BOOK IS FORThose with at least some experience with programming in R.THOMAS MAILUND is Senior Software Architect at Kvantify, a quantum computing company from Denmark. He has a background in math and computer science. He now works on developing algorithms for computational problems applicable for quantum computing. He previously worked at the Bioinformatics Research Centre, Aarhus University, on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species. He has published Beginning Data Science in R with Apress, as well as other books out there.1. Functions in R2. Pure Functional Programming3. Scope and Closures4. Higher-order Functions5. Filer, Map, and Reduce6. Point-free Programming Afterword
Getting Started with SQL and Databases
Learn the basics of writing SQL scripts. Using Standard SQL as the starting point, this book teaches writing SQL in various popular dialects, including PostgreSQL, MySQL/MariaDB, Microsoft SQL Server, Oracle, and SQLite.The book starts with a general introduction to writing SQL and covers the basic concepts. Author Mark Simon then covers database principles, and how database tables are designed. He teaches you how to filter data using the WHERE clause, and you will work with NULL, numbers, dates, and strings. You will also understand sorting results using the ORDER BY clause, sorting by calculated columns, and limiting the number of results. By the end of the book, you will know how to insert and update data, and summarize data with aggregate functions and groups. Three appendices cover differences between SQL dialects, working with tables, and a crash course in PDO.WHAT YOU WILL LEARN* Filter, sort, and calculate data* Summarize data with aggregate functions* Modify data with insert, update, and delete statements* Study design principles in developing a databaseWHO THIS BOOK IS FORDevelopers and analysts working with SQL, as well as web developers who want a stronger understanding of working with databasesMARK SIMON has been involved in training and education since the beginning of his career. He started as a teacher of mathematics but soon moved into IT consultancy and training because computers are much easier to work with than high school students! He has worked with and trained in several programming and coding languages, and currently focuses on web development and database languages. When not involved in work, you will generally find Mark listening to or playing music, reading, or just wandering about.The appendix will include:* Notes on using SQL with PHP* “Cultural Notes” - a description of some of the sample data* Major Differences between DBMSs* Setting up the Sample Database
Hands-on Guide to Apache Spark 3
This book explains how to scale Apache Spark 3 to handle massive amounts of data, either via batch or streaming processing. It covers how to use Spark’s structured APIs to perform complex data transformations and analyses you can use to implement end-to-end analytics workflows.This book covers Spark 3's new features, theoretical foundations, and application architecture. The first section introduces the Apache Spark ecosystem as a unified engine for large scale data analytics, and shows you how to run and fine-tune your first application in Spark. The second section centers on batch processing suited to end-of-cycle processing, and data ingestion through files and databases. It explains Spark DataFrame API as well as structured and unstructured data with Apache Spark. The last section deals with scalable, high-throughput, fault-tolerant streaming processing workloads to process real-time data. Here you'll learn about Apache Spark Streaming’s execution model, the architecture of Spark Streaming, monitoring, reporting, and recovering Spark streaming. A full chapter is devoted to future directions for Spark Streaming. With real-world use cases, code snippets, and notebooks hosted on GitHub, this book will give you an understanding of large-scale data analysis concepts--and help you put them to use.Upon completing this book, you will have the knowledge and skills to seamlessly implement large-scale batch and streaming workloads to analyze real-time data streams with Apache Spark.WHAT YOU WILL LEARN* Master the concepts of Spark clusters and batch data processing* Understand data ingestion, transformation, and data storage* Gain insight into essential stream processing concepts and different streaming architectures* Implement streaming jobs and applications with Spark StreamingWHO THIS BOOK IS FORData engineers, data analysts, machine learning engineers, Python and R programmersALFONSO ANTOLÍNEZ GARCÍA is a senior IT manager with a long professional career serving in several multinational companies such as Bertelsmann SE, Lafarge, and TUI AG. He has been working in the media industry, the building materials industry, and the leisure industry. Alfonso also works as a university professor, teaching artificial intelligence, machine learning, and data science. In his spare time, he writes research papers on artificial intelligence, mathematics, physics, and the applications of information theory to other sciences. Part I. Apache Spark Batch Data ProcessingChapter 1: Introduction to Apache Spark for Large-Scale Data Analytics1.1. What is Apache Spark?1.2. Spark Unified Analytics1.3. Batch vs Streaming Data1.4. Spark EcosystemChapter 2: Getting Started with Apache Spark2.2. Scala and PySpark Interfaces2.3. Spark Application Concepts2.4. Transformations and Actions in Apache Spark2.5. Lazy Evaluation in Apache Spark2.6. First Application in Spark2.7. Apache Spark Web UIChapter 3: Spark Dataframe APIChapter 4: Spark Dataset APIChapter 5: Structured and Unstructured Data with Apache Spark5.1. Data Sources5.2. Generic Load/Save Functions5.3. Generic File Source Options5.4. Parquet Files5.5. ORC Files5.6. JSON Files5.7. CSV Files5.8. Text Files5.9. Hive Tables5.10. JDBC To Other DatabasesChapter 6: Spark Machine Learning with MLlibPart II. Spark Data StreamingChapter 7: Introduction to Apache Spark Streaming7.1. Apache Spark Streaming’s Execution Model7.2. Stream Processing Architectures7.3. Architecture of Spark Streaming: Discretized Streams7.4. Benefits of Discretized Stream Processing7.4.1. Dynamic Load Balancing7.4.2. Fast Failure and Straggler RecoveryChapter 8: Structured Streaming8.1. Streaming Analytics8.2. Connecting to a Stream8.3. Preparing the Data in a Stream8.4. Operations on a Streaming DatasetChapter 9: Structured Streaming Sources9.1. File Sources9.2. Apache Kafka Source9.3. A Rate SourceChapter 10: Structured Streaming Sinks10.1. Output Modes10.2. Output Sinks10.3. File Sink10.4. The Kafka Sink10.5. The Memory Sink10.6. Streaming Table APIs10.7. Triggers10.8. Managing Streaming Queries10.9. Monitoring Streaming Queries10.9.1. Reading Metrics Interactively10.9.2. Reporting Metrics programmatically using Asynchronous APIs10.9.3. Reporting Metrics using Dropwizard10.9.4. Recovering from Failures with Checkpointing10.9.5. Recovery Semantics after Changes in a Streaming QueryChapter 11: Future Directions for Spark Streaming11.1. Backpressure11.2. Dynamic Scaling11.3. Event time and out-of-order data11.4. UI enhancements11.5. Continuous ProcessingChapter 12: Watermarks. A deep survey of temporal progress metrics
Generative AI
This book will show how generative technology works and the drivers. It will also look at the applications – showing what various startupsand large companies are doing in the space. There will also be a look at the challenges and risk factors.During the past decade, companies have spent billions on AI. But the focus has been on applying the technology to predictions – which is known as analytical AI. It can mean that you receive TikTok videos that you cannot resist. Or analytical AI can fend against spam or fraud or forecast when a package will be delivered. While such things are beneficial, there is much more to AI. The next megatrend will be leveraging the technology to be creative. For example, you could take a book and an AI model will turn it into a movie – at very little cost. This is all part of generative AI. It’s still in the nascent stages but it is progressing quickly. Generative AI can already create engaging blog posts, social media messages, beautiful artwork and compelling videos.The potential for this technology is enormous. It will be useful for many categories like sales, marketing, legal, product design, code generation, and even pharmaceutical creation.WHAT YOU WILL LEARNThe importance of understanding generative AIThe fundamentals of the technology, like the foundation and diffusion modelsHow generative AI apps workHow generative AI will impact various categories like the law, marketing/sales, gaming, product development, and code generation.The risks, downsides and challenges.WHO THIS BOOK IS FORProfessionals that do not have a technical background. Rather, the audience will be mostly those in Corporate America (such as managers) as well as people in tech startups, who will need an understanding of generative AI to evaluate the solutions.Tom Taulli is the founder of AICruncher.com, which is a developer of generative AI and ChatGPT tools for business. He is also the author of various books, including Artificial Intelligence Basics: A Non-Technical Introduction and The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems. Tom has a science fiction novel about AI – called Automated -- that will come out later in 2023.Chapter 1: Introduction to Generative AI.- Chapter 2: Data.- Chapter 3: AI Fundamentals.- Chapter 4: Core Generative AI Technology.- Chapter 5: Large Language Models.- Chapter 6: Auto Code Generation.- Chapter 7: The Transformation of Business.- Chapter 8: The Impact on Major Businesses.- Chapter 9: The Future.
Designing Applications for Google Cloud Platform
Learn how to use Google Cloud Platform (GCP) and its services to design, build, and deploy applications. This book includes best practices, practical examples, and code snippets written in Java, making it a key resource for developers seeking hands-on experience with GCP.You'll begin with an introduction to GCP services and a review of what Java offers while developing applications for GCP. Next, you'll be walked through how to set up Google App Engine, Google Storage Cloud, and Google Cloud SQL with use cases, as well as application development and deployment. As the book progresses, you'll be exposed to advanced GCP services, deploying and scaling applications on GCP services, and troubleshooting and optimization of Java applications on GCP. The book uses real-world examples to help you understand how GCP services can solve everyday problems.After completing this book, you will understand Google Cloud Platform and its services, and will have the knowledge needed to design, build, and deploy your own applications on GCP using Java.WHAT YOU'LL LEARN* Create a GCP project, configure authentication and authorization, and deploy a sample application.* Use GCP services to solve common problems and apply them to real-world scenarios* Implement GCP services such as Datastore, SQL, and Spanner* Leverage GCP tools such as the SDK and Cloud ShellWHO THIS BOOK IS FORSoftware developers, Cloud architects, and managers looking to design and build applications for Google Cloud Platform. This book is for those with software development experience who are familiar with Java programming. It is also suitable for those new to GCP who have a basic understanding of cloud computing concepts.ASHUTOSH SHASHI is a TOGAF 9 certified enterprise architect, a seasoned software engineer, and a cloud architect with over 18 years of experience in the industry. He has worked on multiple projects using various technologies and platforms, from small startups to large enterprise systems. He has helped many organizations design and build robust and scalable applications on GCP. Apart from GCP, he has extensive experience and expertise in AWS and Azure cloud platforms. Ashutosh lives in Duluth, Georgia, US. In his free time, he enjoys hiking and spending time with his family. He also loves to travel and explore different cultures.Chapter 1: Introduction to Google Cloud Platform.- Chapter 2: Setting up the Development Environment.- Chapter 3: Google App Engine.- Chapter 4: Data Storage in Google Cloud.- 5: Google Cloud SQL.- Chapter 6: Advanced GCP Services.- Chapter 7: Deployment and Scaling.- Chapter 8: Troubleshooting and Optimization.- Chapter 9: Conclusion.
Ökonometrie und maschinelles Lernen
Für empirische Wirtschaftswissenschaftler gehören ökonometrische Methoden zum Standardwerkzeug. Die neuen Instrumente des maschinellen Lernens setzen sich langsam auch in der Volks- und Betriebswirtschaftslehre durch. Das Buch vermittelt Basiswissen zu den spezifischen Methoden des überwachten und unüberwachten Lernens sowie des Verstärkungslernens. Dabei werden die wesentlichen Unterschiede in Bezug auf Ziele, Methoden und Rahmenbedingungen zwischen den Methoden der Ökonometrie und des maschinellen Lernens dargestellt und erörtert. Einleitung.- Grundlagen des maschinellen Lernens.- Phasenschema.- Anwendungsbereiche.- Fazit.
Kryptografie in der Praxis
Eine Einführung in die bewährten Tools, Frameworks und Protokolle. Moderne Kryptografie kompetent vermittelt.Die Kryptografie ist die wesentliche Grundlage der IT-Sicherheit. Um den Angreifern auf Ihre Systeme einen Schritt voraus zu sein, müssen Sie die Tools, Frameworks und Protokolle verstehen, die Ihre Netzwerke und Anwendungen schützen.Dieses Buch führt in einfacher Sprache und mit anschaulichen Illustrationen in Authentifizierung, Verschlüsselung, Signaturen, Geheimhaltung und andere Kryptografiekonzepte ein. Es enthüllt die kryptografischen Techniken, die die Sicherheit von Web-APIs, die Registrierung und Anmeldung von Benutzern und sogar die Blockchain bestimmen. Sie erfahren, wie diese Techniken moderne Sicherheit ermöglichen und wie Sie sie in Ihren eigenen Projekten anwenden können. Neben den modernen Methoden nimmt das Buch auch die Zukunft der Kryptografie vorweg und geht auf neue und innovative Entwicklungen wie Kryptowährungen und Post-Quantum-Kryptografie ein. Alle Techniken sind vollständig mit Diagrammen und Beispielen illustriert, sodass Sie leicht erkennen können, wie sie in die Praxis umgesetzt werden können.»Mit der richtigen Balance aus Theorie und Praxis vermittelt der Autor genau das, was Softwareschaffende über Kryptografie wissen müssen. Viele kleine Übungen helfen ihnen, von der durchaus anspruchsvollen Lektüre zu profitieren.« - Maik Schmidt, c't 17/23Über den Autor:David Wong ist leitender Kryptografie-Ingenieur bei O(1) Labs und arbeitet an der Kryptowährung Mina. Davor war er Sicherheitsverantwortlicher für die Kryptowährung Diem (vormals bekannt als Libra) bei Novi, Facebook, und davor Sicherheitsberater bei der NCC Group im Bereich Kryptografiedienste.Im Laufe seiner Karriere hat David Wong an mehreren öffentlich finanzierten Open-Source-Audits teilgenommen, beispielsweise an OpenSSL und Let’s Encrypt. Er war Sprecher auf verschiedenen Konferenzen, einschließlich Black Hat und DEF CON, und hat in einem regelmäßig stattfindenden Kryptografiekurs bei Black Hat unterrichtet. Hervorzuheben sind seine Beiträge zu Standards wie TLS 1.3 und zum Noise Protocol Framework. Er hat Schwachstellen in vielen Systemen gefunden, einschließlich CVE-2016-3959 in der Golang-Standardbibliothek, CVE-2018-12404, CVE-2018-19608, CVE-2018-16868, CVE-2018-16869 und CVE-2018-16870 in verschiedenen TLS-Bibliotheken.Unter anderem ist er Autor des Disco-Protokolls (www.discocrypto.com und www.embeddeddisco.com) und des Decentralized Application Security Project für Smart Contracts (www.dasp.co). Zu seinen Forschungen gehören Cache-Angriffe auf RSA (http://cat.eyalro.net), ein auf QUIC basierendes Protokoll (https://eprint.iacr.org/2019/028), Timing-Angriffe auf ECDSA (https://eprint.iacr.org/2015/839) oder Hintertüren in Diffie-Hellman (https://eprint.iacr.org/2016/644). Aktuell finden Sie ihn in seinem Blog unter www.cryptologie.net.
Quantitative User Experience Research
This book is your definitive guide to the rapidly growing role of Quantitative User Experience (Quant UX) Research in product development. The book provides an overview of the skills you need on the job, presents hands-on projects with reusable code, and shares advice on starting and developing a career. The book goes beyond basic skills to focus on what is unique to Quant UX. The authors are two of the most widely recognized practitioners in Quant UX research, and this book shares insights from their combined decades of experience.Organizations today have more data about user needs and behaviors than ever before. With this large-scale data, Quant UX researchers work to understand usage patterns, measure the impact of design changes, and inform strategic decisions. In the Quant UX role, interdisciplinary researchers apply analytical skills to uncover user needs, inform engineering and design, answer strategic business questions, and optimize software and hardware products for human interaction. This book provides guidance around customer satisfaction surveys, understanding user behavior from log analysis, and the statistical methods that are commonly used to assess user outcomes.WHAT YOU WILL LEARN* Discover the role of Quantitative User Experience (Quant UX) research* Understand how Quant UX research differs from other disciplines such as data science* Plan common research projects and know how to achieve success* Position Quant UX activities in product development, engineering, and UX organizations* Apply the HEART framework to measure user experience outcomes* Evaluate your skills and potential to be hired as a Quant UX researcher* Know what to expect during job interviews* Find examples of common Quant UX projects with shared R code and data setsWHO THIS BOOK IS FORPractitioners and managers who seek a comprehensive guide to the new field of Quantitative User Experience Research. Readers will understand the Quant UX role, build research skills, find examples of hands-on code and analyses, learn about UX organizations and stakeholders, and receive advice on job interviews and career paths. Data scientists, social scientists, and other researchers will learn how their skills transfer to Quant UX, where they can help teams build better, more successful products.CHRIS CHAPMAN, PhD, is a Principal UX Researcher at Amazon Lab126, the Founder and Co-chair of the Quant UX Conference, and President of the Quantitative User Experience Association. Chris is the co-author of two popular Springer books on programming and analytics: R for Marketing Research and Analytics and Python for Marketing Research and Analytics. As a psychologist, Chris emphasizes the human focus of research and the need for integrated quantitative and qualitative understanding of users.KERRY RODDEN, PhD, is a Senior Principal Researcher at Code for America. Kerry founded the Quantitative UX Research role at Google in 2007 and managed the industry's first Quant UX research team. Kerry has originated popular tools and techniques, including the HEART metrics framework for user experience, and the sequences sunburst visualization of user behavior. Kerry’s background is in computer science and human-computer interaction, with a focus on the analysis and visualization of large-scale usage data, including A/B testing.IntroductionPART I. USER EXPERIENCE (UX) AND QUANT UX1. Getting Started2. User Experience (UX) and UX Research3. Quantative UX Research: OverviewPART II. CORE SKILLS4. UX Research5. Statistics6. ProgrammingPART III. TOOLS AND TECHNIQUES7. Metrics of User Experience8. Customer Satisfaction Surveys9. Log Sequence Visualization10. MaxDiff: Prioritizing Features and User NeedsPART IV. ORGANIZATIONS AND CAREERS11. UX Organization Structures12. Interviews and Job Postings13. Research Processes, Reporting, and Stakeholders14. Career Development for Quant UX Researchers15. Future Directions for Quant UXAPPENDIX A: Example Quant UX Job DescriptionAPPENDIX B: Example Quant UX Hiring RubricsAPPENDIX C: References