Computer und IT
Microsoft 365 Excel VBA Programming For Dummies
YOUR STEP-BY-STEP GUIDE TO DOING MORE WITH MICROSOFT EXCELFully updated for the latest version of Office 365, Excel VBA Programming For Dummies will take your Excel knowledge to the next level. With a little background in Visual Basic for Applications (VBA) programming, you can go well beyond basic spreadsheets and functions. Learn the coding basics and syntax you need to write simple or complex macros that can automate your routine Excel tasks. Become an Excel power user by automating data management, user forms, pivot tables, and beyond. When you use VBA to perform Excel operations, you can reduce errors, save time, and integrate with other Microsoft applications. This handy guide also teaches you how to control the security settings for your macros and save macros to use across files and apps. Plus, you'll get updated coverage of Copilot AI integration. Your spreadsheets are about to get much more powerful.* Get stared with VBA coding to create macros and automate tasks in Excel* Follow step-by-step instructions to write and execute your first scripts* Learn about the advanced functions available with the VBA language* Perform tasks faster and integrate excel with other Microsoft appsThis Dummies guide is right up your alley if you're an Excel user looking to learn some next-level features. Students and professionals alike will reap the benefits of automation, thanks to Excel VBA Programming For Dummies.DICK KUSLEIKA has more than 25 years’ experience helping Office users get the most out of Microsoft’s bestselling software. From online forums to blogs, books, and conferences, he delivers sound and straightforward advice to readers of all skill levels.
Microsoft 365 Word For Dummies
TAKE A DEEP DIVE INTO THE MOST POPULAR WORD PROCESSOR ON THE PLANETWord, Microsoft's powerful and popular word processor, is capable of extraordinary things. From template building to fancy formatting and even AI-powered editing and proofing, your copy of Word stands ready to help you supercharge your productivity and save you time and energy. You just need to learn how it's done. And, thanks to this easy-to-understand book, learning is the easy part!This latest edition of Word For Dummies is packed with the essentials you need to turn any old copy of the famous word processor into a document-creating, table-formatting, graphics-editing super app. You'll even learn how to customize your version of Microsoft Word so it's absolutely perfect for you, at home and at work. You'll also find out how to:* Navigate the Word interface and menus and figure out a ton of hotkey shortcuts* Edit, format, and comment documents to make team collaboration a breeze* Use the new Microsoft Copilot's AI capabilities to make Word even more powerfulSo, grab your copy of the latest edition of Word For Dummies today. It's perfect for casual users interested in upgrading their knowledge of this ubiquitous app as well as power users looking for the latest productivity tips and tricks. DAN GOOKIN wrote the first-ever For Dummies book in 1991. The author of several bestsellers, Dan’s books have been translated into 32 languages and have more than 11 million copies in print. Dan is the bestselling author of all editions of Word For Dummies.
Microsoft Teams For Dummies
UNLOCK THE FULL POWER OF MICROSOFT TEAMS, INCLUDING BRAND-NEW AI FUNCTIONALITY, WITH YOUR FRIENDS AT FOR DUMMIESLooking for a fast and easy guide to Microsoft Teams, the collaboration software used by millions of people and companies around the world? In Microsoft Teams For Dummies, 3rd edition, you'll find the must-know tips, hidden tricks, and handy hacks you need to help you rock your workday and get things done lightning-fast. You'll learn how to incorporate Teams into your everyday workflow and use functionality like chatting, file sharing, team organization, videochat, and more. You'll even learn how to use Microsoft's brand-new AI companion Copilot to help you improve your processes and productivity. You'll find out how to:* Connect with colleagues and collaborate remotely, from across the hall or from the other side of the world* Use little-known Teams features to help you supercharge your productivity and get more done in a day* Customize your Teams installation and make it work better for you and your teammatesAn engaging and effective roadmap to one of Microsoft's most popular apps, Microsoft Teams For Dummies is a must-read for everyone who uses—or wants to use—this powerful software at work or anywhere else. Grab a copy today! ROSEMARIE WITHEE is president of Portal Integrators, a Scrum-based software and services firm. Rosemarie has authored a number of books in the For Dummies series, including the most recent editions of Office 365 For Dummies and SharePoint For Dummies.
Microsoft Copilot For Dummies
STRAIGHTFORWARD GUIDANCE ON THE AI TOOL THAT'S BUILT INTO WINDOWS, MICROSOFT 365, AND MOREMicrosoft is enhancing all its most widely used productivity software—including Windows and apps like Word and Excel—with the power of AI. And now you can learn to make the most of this revolutionary new tool with Microsoft Copilot For Dummies!You'll discover how to write Copilot-friendly prompts, enhance output with integrated Copilot tools, and how to apply Copilot functions to project management and other specific tasks and disciplines. In the book, you'll find out how to:* Use text or your voice to prompt reliable results from Microsoft Copilot* Customize Microsoft Copilot to respond to your unique needs and demands* Add plug-ins to the Microsoft Copilot service to extend its functionality even moreLearn to supercharge your efficiency with Microsoft Copilot For Dummies. This book is perfect for professional and home users of Windows, Microsoft 365, and other Microsoft products and software who want to increase their productivity. Grab a copy today! CHRIS MINNICK is an accomplished author, teacher, and programmer. Minnick has authored or coauthored over 20 books, including titles in the For Dummies series. He has developed video courses for online training providers, and he teaches programming and machine learning to professional developers at leading companies globally. He is author of Coding with AI For Dummies and JavaScript All-in-One For Dummies.
Generative AI Apps with LangChain and Python
Future-proof your programming career through practical projects designed to grasp the intricacies of LangChain’s components, from core chains to advanced conversational agents. This hands-on book provides Python developers with the necessary skills to develop real-world Large Language Model (LLM)-based Generative AI applications quickly, regardless of their experience level.Projects throughout the book offer practical LLM solutions for common business issues, such as information overload, internal knowledge access, and enhanced customer communication. Meanwhile, you’ll learn how to optimize workflows, enhance embedding efficiency, select between vector stores, and other optimizations relevant to experienced AI users. The emphasis on real-world applications and practical examples will enable you to customize your own projects to address pain points across various industries._Developing LangChain-based Generative AI LLM Apps with Python_ employs a focused toolkit (LangChain, Pinecone, and Streamlit LLM integration) to practically showcase how Python developers can leverage existing skills to build Generative AI solutions. By addressing tangible challenges, you’ll learn-by-be doing, enhancing your career possibilities in today’s rapidly evolving landscape.WHAT YOU WILL LEARN* Understand different types of LLMs and how to select the right ones for responsible AI.* Structure effective prompts.* Master LangChain concepts, such as chains, models, memory, and agents.* Apply embeddings effectively for search, content comparison, and understanding similarity.* Setup and integrate Pinecone vector database for indexing, structuring data, and search.* Build Q & A applications for multiple doc formats.* Develop multi-step AI workflow apps using LangChain agents.WHO THIS BOOK IS FORPython programmers who aim to develop a basic understanding of AI concepts and move from LLM theory to practical Generative AI application development using LangChain; those seeking a structured guide to enhance their careers by learning to create robust, real-world LLM-powered Generative AI applications; data scientists, analysts, and experienced developers new to LLMs.RABI JAY has over 15 years of experience driving digital transformation with a unique blend of technical depth and business acumen. His background as a Java and SAP ABAP developer provides insights into the enterprise systems LLMs often needed to integrate with. As a leader in Deloitte’s Digital / Cloud Native practice, he has gained cross-industry experience applying AI solutions, positioning him to identify where LLMs offer the greatest potential for business impact.He is passionate about making complex technology accessible, leading him to authoring books on SAP NetWeaver Portal Technology and "Enterprise AI in the Cloud" along with regular contributions to industry publications. His role as a technical reviewer for Large Language Model Based Solutions, Modern Python Development Using ChatGPT, and as Vice President at HCL America, focused on digital transformation, demonstrate his active engagement in the LLM field. Additionally, he runs a LinkedIn newsletter ("Enterprise AI Transformation") and free LinkedIn course (“Generative AI for Business Innovation”).Chapter 1: Introduction to LangChain and LLMs.- Chapter 2: Integrating LLM APIs with LangChain.- Chapter 3: Building Q&A and Chatbot Apps.- Chapter 4: Exploring LLMs.- Chapter 5: Mastering Prompts for Creative Content.- Chapter 6: Building Chatbots and Automated Analysis Systems Using Chains.- Chapter 7: Building Advanced Q&A and Search applications Using Retrieval-Augmented Generation (RAG).- Chapter 8: Your First Agent App.- Chapter 9: Building Different Types of Agents.- Chapter 10: Projects: Building Agent Apps for Common Use Cases. - Chapter 11: Building & Deploying a ChatGPT Like App Using Streamlit.
Hands-on Deep Learning
This book discusses deep learning, from its fundamental principles to its practical applications, with hands-on exercises and coding. It focuses on deep learning techniques and shows how to apply them across a wide range of practical scenarios.The book begins with an introduction to the core concepts of deep learning. It delves into topics such as transfer learning, multi-task learning, and end-to-end learning, providing insights into various deep learning models and their real-world applications. Next, it covers neural networks, progressing from single-layer perceptrons to multi-layer perceptrons, and solving the complexities of backpropagation and gradient descent. It explains optimizing model performance through effective techniques, addressing key considerations such as hyperparameters, bias, variance, and data division. It also covers convolutional neural networks (CNNs) through two comprehensive chapters, covering the architecture, components, and significance of kernels implementing well-known CNN models such as AlexNet and LeNet. It concludes with exploring autoencoders and generative models such as Hopfield Networks and Boltzmann Machines, applying these techniques to a diverse set of practical applications. These applications include image classification, object detection, sentiment analysis, COVID-19 detection, and ChatGPT.By the end of this book, you will have gained a thorough understanding of deep learning, from its fundamental principles to its innovative applications, enabling you to apply this knowledge to solve a wide range of real-world problems.WHAT YOU WILL LEARN* What are deep neural networks?* What is transfer learning, multi-task learning, and end-to-end learning?* What are hyperparameters, bias, variance, and data division?* What are CNN and RNN?WHO THIS BOOK IS FORMachine learning engineers, data scientists, AI practitioners, software developers, and engineers interested in deep learningHARSH BHASIN is a researcher and practitioner. He has completed his PhD in Diagnosis and Conversion Prediction of Mild Cognitive Impairment Using Machine Learning from Jawaharlal Nehru University, New Delhi. He worked as a Deep Learning consultant for various firms and taught at various Universities, including Jamia Hamdard, and DTU. He is currently associated with Bennett University.Harsh has authored 11 books, including _Programming in C#_ and _Algorithms._ He has authored more than 40 papers that have been published in international conferences and renowned journals, including Alzheimer’s and Dementia, Soft Computing, Springer, BMC Medical Informatics & Decision Making, AI & Society, etc. He is the reviewer of a few renowned journals and has been the editor of a few special issues. He has been a recipient of Visvesvaraya Fellowship, Ministry of Electronics and Information Technology.His areas of expertise include Deep Learning, Algorithms and Medical Imaging. Apart from his professional endeavours, he is deeply interested in Hindi Poetry: the progressive era and Hindustani Classical Music: percussion instruments.Chapter 1: Revisiting Machine Learning.- Chapter 2: Introduction to Deep Learning.- Chapter 3: Neural Networks.- Chapter 4: Training Deep Networks.- Chapter 5: Hyperparameter Tuning.- Chapter 6: Convolutional Neural Networks: Part 1.- Chapter 7: Convolutional Neural Networks : Part 2.- Chapter 8: Transfer Learning.- Chapter 9: Recurrent Neural Networks.- Chapter 10: LSTM and GRU.- Chapter 11: Autoencoders.- Chapter 12: Introduction to Generative Models.- Appendices A-G.
Java 23 for Absolute Beginners
Write your first code in Java 23 using simple, step-by-step examples that model real-word objects and events, making learning easy. With this book you will be able to pick up core programming concepts without fuss and write efficient Java code in no time. Clear code descriptions and layout ensure you get your code running as soon as possible. Author Iuliana Cosmina focuses on practical knowledge and getting you up to speed quickly—all the bits and pieces a novice needs to get started programming in Java.In this edition, you will discover how Java has changed since version 17, and how to design and write code using the most recently introduced Java features such as new collection methods, virtual threads, pattern and record matching in switch expressions, structured concurrency tasks, unnamed classes and instance methods, and many more.This book is a complete Java guide, covering the following topics: setting up a development environment, programming concepts and well-known programming principles, writing Java code following industry-specific design patterns and coding conventions, executing it, debugging, testing, documenting it and even using specialized tools such as IntelliJ IDEA for writing Java code, Maven for building, JUnit Jupiter for testing, and in-memory and Docker-hosted databases or data storage. After reading this book, you’ll have all the necessary skills and knowledge to pass an interview for a starting Java development position.WHAT YOU WILL LEARN* Set up a Java development environment* Use the Java language to write high-quality code* Understand fundamental programming concepts and algorithms* Use virtual threads, records, and other Java renown features* Debug, test, and document Java code* Improve performance by customizing the Garbage CollectorWHO THIS BOOK IS FORThose who are new to programming and want to learn Java and use it to build efficient solutionsIULIANA COSMINA is currently a software engineer for Cloudsoft, Edinburgh. She has been writing Java code since 2002 and contributed to various types of applications such as experimental search engines, ERPs, track and trace, and banking. During her career, she has been a teacher, a team leader, software architect, DevOps professional, and software manager. She is a Spring-certified Professional, as defined by Pivotal, the makers of Spring Framework, Boot, and other tools, and considers Spring the best Java framework to work with. When she is not programming, she spends her time reading, blogging, learning to play piano, travelling, hiking, or biking.1. An Introduction to Java and its History.- 2. Preparing your Development Environment.- 3. Getting Your Feet Wet.- 4. Java Syntax.- 5. Data Types.- 6. Operators.- 7. Controlling the Flow.- 8. The Stream API.- 9. Debugging, Testing, and Documenting.- 10. Making Your Application Interactive.- 11. Working With Files.- 12. The Publish-Subscribe Framework.- 13. Garbage Collection.- Appendix A.
Mensch-Computer-Interaktion (3. Auflage)
Jeder hat das schon einmal erlebt: Webseiten, auf denen man die Schrift nicht lesen kann, Informationsterminals, bei denen man nicht erkennt, wo man drücken soll, Programme, die unverständliche Meldungen hervorbringen, kurz: Software, die nicht gebrauchstauglich ist. Dieses Buch enthält Basiswissen, das alle benötigen, die gebrauchstaugliche Software erstellen wollen. Ausgehend von der menschlichen Informationsverarbeitung erläutern die Autoren, wie Benutzungsschnittstellen beschaffen sein müssen und wie bei der Entwicklung von Anwendungen vorzugehen ist, damit Menschen die Software sinnvoll nutzen können. Das Buch berücksichtigt die aktuellen Normen und Vorschriften anhand praktischer Beispiele. Diese dritte erweiterte und komplett überarbeitete Auflage integriert neben aktuellen technologischen Entwicklungen auch die Erfahrungen aus mehr als 20 Jahren Lehre in der Mensch-Computer-Interaktion.Auf der Webseite mci-buch.info sind Lösungen zu den Aufgaben, weitere Beispiele und Übungsaufgaben, inhaltliche Ergänzungen, und weiterführende Links zu finden. Probleme bei der Rechnerbenutzung. Ergonomie in der Mensch-Computer-Interaktion. Die Benutzungsschnittstelle. Entwicklung gebrauchstauglicher Systeme. Physiologie der menschlichen Informationsverarbeitung. Psychologie der menschlichen Informationsverarbeitung. Handlungsprozesse. Standardausgabegeräte. Standardeingabegeräte. Ein- und Ausgabe räumlicher Daten. Nicht visuelle Interaktionsmodalitäten. Gestaltungsprinzipien für Benutzungsschnittstellen. Informationsdarstellung. Visuelle Interaktionselemente. Dialoggestaltung. Benutzerunterstützung. Berücksichtigung spezifischer Benutzerbedürfnisse. DR. ANDREAS M. HEINECKE war bis Ende Februar 2022 hauptamtlich als Professor für interaktive Systeme am Fachbereich Informatik und Kommunikation der Westfälischen Hochschule in Gelsenkirchen tätig. In seinen Lehrveranstaltungen, in der Praxis als Berater und Entwickler sowie in zahlreichen wissenschaftlichen Veröffentlichungen befasst er sich mit Mensch-Computer-Interaktion insbesondere bei multimedialen und mobilen Anwendungen.DR. JENS GERKEN ist seit Juli 2023 Professor für das Fachgebiet Inklusive Mensch-Roboter-Interaktion an der TU Dortmund und beschäftigt sich dort unter anderem mit Fragen der Zugänglichkeit und Barrierefreiheit interaktiver Technologien. Zwischen 2015 und 2023 war er zuvor als Professor für Mensch-Computer-Interaktion am Fachbereich Informatik und Kommunikation der Westfälischen Hochschule in Gelsenkirchen tätig.
Programmieren mit JavaScript
JavaScript hat sich mittlerweile von einer, am Anfang teils nicht ganz ernst genommenen, Skriptsprache im Browser zu einer der wichtigsten Programmiersprachen überhaupt entwickelt. Im Kern immer noch als die Sprache im Webbrowser schlechthin populär, erobert JavaScript nach und nach immer mehr Anwendungsgebiete. Bei der clientseitigen Webentwicklung gibt es im Grunde keine Alternative zu JavaScript für die Entwicklung interaktiver und dynamischer Webanwendungen. Nahezu alle Frameworks basieren zudem auf JavaScript. Aber auch zur Unterstützung vieler weiterer Arten von Software kann man JavaScript einsetzen bzw. gibt es auf JavaScript aufsetzende Frameworks.Insbesondere boomt aber die serverseitige Entwicklung mit JavaScript. Beispielsweise mit Node.js können Entwickler JavaScript auf Serverseite ausführen, was die Entwicklung von skalierbaren und leistungsstarken Webanwendungen ermöglicht. Node.js wird zudem häufig für die Erstellung von APIs, Echtzeit-Anwendungen und Microservices verwendet.Entdecken Sie in diesem Buch nun die mittlerweile fast grenzenlosen Möglichkeiten von JavaScript. Von den Grundlagen bis hin zu fortgeschrittenen Techniken werden alle Aspekte der Sprache abgedeckt. Tauchen Sie ein in die Welt von JavaScript und erweitern Sie Ihr Wissen mit praxisnahen Beispielen und bewährten Methoden. Egal, ob Sie mit JavaScript beginnen und die Grundlagen erlernen möchten, oder als erfahrene(r) Entwicklerin bzw. Entwickler das Können vertiefen wollen. Hier finden Sie das Wissen und die Werkzeuge, um Ihre JavaScript-Fähigkeiten auf das nächste Level zu bringen. Einleitung. Erste Beispiele – Der Sprung ins kalte Wasser. Versionen von JavaScript und Einbindung in Webseiten. Elementare JavaScript-Grundstrukturen. Kontrollflussanweisungen. Arrays, JSON und andere iterierbare Elemente. Funktionen, Prozeduren und Methoden. Module. Objekte und JavaScript. Eingebaute Objektdeklarationen. Der DOM – das Mysterium der JavaScript-Welt. Ausnahmebehandlung. Asynchrone Programmierung. Erweiterte Techniken. Eine Frage der Qualität. RALPH STEYER wurde in Wiesbaden geboren und hat nach dem Abitur in Frankfurt Mathematik studiert. Seit 1996 arbeitet er selbstständig als Diplom-Mathematiker im Bereich EDV-Schulung, Programmierung und Beratung. Seine Spezialgebiete sind Internetprogrammierung und objektorientierte Software-Entwicklung. Unter anderem unterrichtet er an Hochschulen sowie für verschiedene Schulungsanbieter. Ralph Steyer ist zudem Autor zahlreicher Fachbücher und Videotrainings zu verschiedenen Programmierthemen.
Spiele programmieren mit Scratch
* 12 COOLE COMPUTERSPIELE GANZ EINFACH MIT SCRATCH ERSTELLEN* VON DEN GRUNDLAGEN BIS ZU CLEVEREN TRICKS WIE BERÜHRUNGEN ERKENNEN UND PUNKTE ZÄHLEN * FÜR KINDER AB 9 JAHREN OHNE VORKENNTNISSE* AKTUELL ZU SCRATCH 3.0Mit diesem Buch lernen Kinder ganz einfach und spielerisch das Programmieren. Hierzu ist nichts weiter nötig als ein PC, die kostenlose Programmiersprache Scratch und dieses Buch.Scratch ist eine visuelle Programmiersprache und damit besonders gut für Kinder und die ersten Gehversuche in der Welt der Programmierung geeignet. Das Buch enthält eine kurze Einführung in die Verwendung von Scratch sowie Anleitungen für 12 spannende Spiele, die Kinder ganz leicht selbstständig umsetzen können. Durch die intuitive Bedienung von Scratch können die Spiele einfach angepasst werden, um der eigenen Kreativität freien Lauf zu lassen.Während sie die Spiele aus dem Buch umsetzen, lernen Kinder spielerisch wichtige Grundlagen der Programmierung wie z.B. die Funktionsweise von Schleifen, Variablen und Funktionen, die später auf andere Programmiersprachen übertragen werden können.Für das Programmieren kleiner Spiele unterwegs enthält das Buch zusätzlich eine kurze Einführung in die Smartphone-App ScratchJr.SPIELE IM BUCH:* Zahlenraten* Versteckspiel* Baseball* Asteroiden abschießen* Tennis* Adventure: Verwunschenes Haus* und viele mehrThomas Kaffka arbeitet als Dozent für IT an einem Gymnasium und in zwei Bildungseinrichtungen, die Schülerinnen und Schülern die IT näherbringen. Er war viele Jahre als Softwareingenieur und Projektleiter in Softwarehäusern sowie Wirtschaftsprüfungs- und Beratungsgesellschaften tätig.
Learning Algorithms for Internet of Things
The advent of Internet of Things (IoT) has paved the way for sensing the environment and smartly responding. This can be further improved by enabling intelligence to the system with the support of machine learning and deep learning techniques. This book describes learning algorithms that can be applied to IoT-based, real-time applications and improve the utilization of data collected and the overall performance of the system.Many societal challenges and problems can be resolved using a better amalgamation of IoT and learning algorithms. “Smartness” is the buzzword that is realized only with the help of learning algorithms. In addition, it supports researchers with code snippets that focus on the implementation and performance of learning algorithms on IoT based applications such as healthcare, agriculture, transportation, etc. These snippets include Python packages such as Scipy, Scikit-learn, Theano, TensorFlow, Keras, PyTorch, and more._Learning Algorithms for Internet of Things _provides you with an easier way to understand the purpose and application of learning algorithms on IoT.WHAT YOU’LL LEARN* Supervised algorithms such as Regression and Classification.* Unsupervised algorithms, like K-means clustering, KNN, hierarchical clustering, principal component analysis, and more.* Artificial neural networks for IoT (architecture, feedback, feed-forward, unsupervised).* Convolutional neural networks for IoT (general, LeNet, AlexNet, VGGNet, GoogLeNet, etc.).* Optimization methods, such as gradient descent, stochastic gradient descent, Adagrad, AdaDelta, and IoT optimization.WHO THIS BOOK IS FORStudents interested in learning algorithms and their implementations, as well as researchers in IoT looking to extend their work with learning algorithmsDR. G. R. KANAGACHIDAMBARESAN is a Professor in the Department of CSE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology. His main research interests includes IoT, Expert systems and Sensors. He has published several reputed articles and undertaken several consultancy activities for leading MNC companies. He has also guest edited several special issue volumes and books at Springer and serves on the editorial review board for peer reviewed journals.He is currently working on several government-sponsored research projects like ISRO, DBT and DST. He is a TEC committee member in DBT. He is an ASEM-DUO Fellow and has successfully edited several books in EAI Springer. He is currently the Editor-in-Chief for the Next Generation Computer and Communication Engineering Series (Wiley). He received his B.E degree in Electrical and Electronics Engineering from Anna University in 2010 and M.E. Pervasive Computing Technologies in Anna University in 2012. He has completed his Ph.D. in Anna University Chennai in 2017.DR. N. BHARATHI is an Associate Professor in the Computer Science Engineering Department at SRM Institute of Science and Technology in Chennai, India. Her past experiences are Associate Professor at Saveetha School of Engineering, R&D head at Yalamanchili Manufacturing Private Limited, and Assistant professor in SASTRA deemed university. She has good knowledge to work with IoT and embedded system in addition to computer science engineering concepts.She was awarded with a Ph.D. degree in Computer Science in 2014 from SASTRA Deemed University, with 19+ years of work experience as an academic and industrial experience as R&D head involved in ARM platform boards with software development in Ubuntu OS. She completed her M. Tech in Advanced computing in SASTRA deemed University and done her M.Tech project internship at Center for High Performance Embedded System (CHiPES), Nanyang Technological University (NTU), Singapore. She was completed her B.E. in computer science engineering in 2002 at Shanmugha College of Engineering (Bharathidasan University). She published many research papers in reputed journals and conferences along with book chapters, advised many B.Tech. and M.Tech. students in various domains of computer science engineering and embedded systems and is currently advising four research scholars.Chapter 1: Learning Algorithms for IoT.- Chapter 2: Python Packages for Learning Algorithms.- Chapter 3: Supervised Algorithms.- Chapter 4: Unsupervised Algorithms.- Chapter 5: Reinforcement Algorithms.- Chapter 6: Artificial Neural Networks for IoT.- Chapter 7: Convolutional Neural Networks for IoT.- Chapter 8: LSTM, GAN, and RNN.- Chapter 9: Optimization Methods.
Snowflake Recipes
Explore Snowflake’s core concepts and unique features that differentiates it from industry competitors, such as, Azure Synapse and Google BigQuery. This book provides recipes for architecting and developing modern data pipelines on the Snowflake data platform by employing progressive techniques, agile practices, and repeatable strategies.You’ll walk through step-by-step instructions on ready-to-use recipes covering a wide range of the latest development topics. Then build scalable development pipelines and solve specific scenarios common to all modern data platforms, such as, data masking, object tagging, data monetization, and security best practices. Throughout the book you’ll work with code samples for Amazon Web Services, Microsoft Azure, and Google Cloud Platform. There’s also a chapter devoted to solving machine learning problems with Snowflake.Authors Dillon Dayton and John Eipe are both Snowflake SnowPro Core certified, specializing in data and digital services, and understand the challenges of finding the right solution to complex problems. The recipes in this book are based on real world use cases and examples designed to help you provide quality, performant, and secured data to solve business initiatives.WHAT YOU’LL LEARN* Handle structured and un- structured data in Snowflake.* Apply best practices and different options for data transformation.* Understand data application development. * Implement data sharing, data governance and security.WHO THIS BOOK IS FORData engineers, scientists and analysts moving into Snowflake, looking to build data apps. This book expects basic knowledge in Cloud (AWS or Azure or GCP), SQL and PythonDillon Dayton is a senior consultant for CDW. Over the last 10 years he has performed in a data engineering and architect role with numerous companies across a slew of industries including healthcare, retail, and finance. Dillon is Snowflake SnowPro Core certified and participates in the Snowflake SME program. In his spare time, he enjoys applying his data and engineering background to hobbies like motorsports, gardening, and fishing.John Eipe is a Senior Solutions Specialist for CDW and has over 10 years of experience in various roles from enterprise application development to data engineering. He worked primarily with customers from the ecommerce and insurance domain. John is Snowflake SnowPro Core certified and has been working extensively on Snowflake in the recent years. Apart from work, he enjoys cooking and time with his kids.Chapter 1: Introduction to Snowflake.- Chapter 2: Bringing Your Data into Snowflake.- Chapter 3: Handling Atypical Data.- Chapter 4: Data Security and Privacy.- Chapter 5: Handling Near and Real Time Data.- Chapter 6: Programmable Data Pipelines.- Chapter 7: Data Reusability and Monetization.- Chapter 8: Data Recovery and Protection.- Chapter 9: Applications Integration.- Chapter 10: Machine Learning.
Project Objectives Management
Manage supplier objectives effectively to align project and organizational success within your organization. This book introduces a dedicated method for suppliers to follow to ensure that all relevant targets and expectations are successfully meet. The method integrates a day-to-day high awareness, urgency, and focus on the management of all relevant objectives within the supplier’s project to provide maximum benefit for its organization.You'll learn that formal targets are routinely established at the start of a project and captured in a contract or project charter. Formal customer expectations, such as timelines, scope, and budget, have high focus and are often pitted against internal day-to-day challenges, such as cost increases and other unexpected changes. These challenges can seem even more daunting as a project progresses, especially when other stakeholders have expectations as well. When not managed properly, this can obstruct the focus of less urgent or informal objectives, such as employee development, process assets, and lessons learned, some of which provide a critical benefit for the supplier’s organization and its future.To combat this, you'll follow detailed instructions on how to handle such potential roadblocks and how to focus on achieving all relevant project objectives by applying the established method. Each chapter expands the dedicated method itself and provides insight into this philosophy. In the end you'll have all the necessary prerequisites for a successful implementation of these principles within your organization.WHAT YOU WILL LEARN* Define organizational objectives aligned with the organization’s purpose and values* Prioritize and align project specific objectives with the organizational objectives* Facilitate to achieve the project objectives* Handle day-to-day challenges with managing the project objectives* Balance customer and supplier targets and expectationsWHO THIS BOOK IS FORProject management professionals with various levels of skill and experience working at small-to-medium sized project suppliers, both for-profit and non-profit organisations.Reitse van der Wekken works as project manager at Allseas, a world-leading contractor in the offshore energy market, where he leads innovative offshore platform decommissioning and installation projects, mostly located on the North Sea in Europe. In 1996 he received his MSc degree in mechanical engineering at the Delft University of Technology in The Netherlands. Thereafter he started working as project manager on international projects at German multinational Siemens, delivering automation, control and electrical systems for harbor cranes. Driven by a long-term interest in offshore engineering and construction, in 2012 Reitse moved on to Allseas. Since then he has continued his research and writing about project objectives management.He lives with his wife and two children in the city of Delft in The Netherlands. When not reading, writing, or relaxing with his family and friends, you might find him at sea sailing. His book _Project Objectives Management _and the project management method introduced in it, is the result of more than two decades of interest and writing about project objectives management, a topic that highly interests and challenges him on a daily basis as a project management professional.Part 1: Why, Towards What, and What?.- Chapter 1: The Customer Perspective – Why Change?.- Chapter 2: The Goal – Where to Change Towards?.- 3 Productive Aspects of Project Subjects – What to Change?.- Part 2: How?.- Chapter 4: The Supplier Perspective – How to Change?.- Chapter 5: Project Objectives – How to Cause this Change?.- Chapter 6: Process – How to Implement this Change?.- 7: Management – How to Integrate this Change?.- 8: Benefits – How to Benefit from this Change?.
Building Scalable Deep Learning Pipelines on AWS
This book is your comprehensive guide to creating powerful, end-to-end deep learning workflows on Amazon Web Services (AWS). The book explores how to integrate essential big data tools and technologies—such as PySpark, PyTorch, TensorFlow, Airflow, EC2, and S3—to streamline the development, training, and deployment of deep learning models.Starting with the importance of scaling advanced machine learning models, this book leverages AWS's robust infrastructure and comprehensive suite of services. It guides you through the setup and configuration needed to maximize the potential of deep learning technologies. You will gain in-depth knowledge of building deep learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.The book provides insights into setting up an AWS environment, configuring necessary tools, and using PySpark for distributed data processing. You will also delve into hands-on tutorials for PyTorch and TensorFlow, mastering their roles in building and training neural networks. Additionally, you will learn how Apache Airflow can orchestrate complex workflows and how Amazon S3 and EC2 enhance model deployment at scale.By the end of this book, you will be equipped to tackle real-world challenges and seize opportunities in the rapidly evolving field of deep learning with AWS. You will gain the insights and skills needed to drive innovation and maintain a competitive edge in today’s data-driven landscape.WHAT YOU WILL LEARN* Maximize AWS services for scalable and high-performance deep learning architectures* Harness the capacity of PyTorch and TensorFlow for advanced neural network development* Utilize PySpark for efficient distributed data processing on AWS* Orchestrate complex workflows with Apache Airflow for seamless data processing, model training, and deploymentWHO THIS BOOK IS FORData scientists looking to expand their skill set to include deep learning on AWS, machine learning engineers tasked with designing and deploying machine learning systems who want to incorporate deep learning capabilities into their applications, AI practitioners working across various industries who seek to leverage deep learning for solving complex problems and gaining a competitive advantageABDELAZIZ TESTAS, PHD, is a seasoned data scientist with over a decade of experience in data analysis and machine learning. He earned his PhD in Economics from the University of Leeds in England and holds a master’s degree in the same field from the University of Glasgow in Scotland. Additionally, he has earned several certifications in computer science and data science in the United States.For over 10 years, Abdelaziz served as a Lead Data Scientist at Nielsen, where he played a pivotal role in enhancing the company’s audience measurement capabilities. He was instrumental in planning, initiating, and executing end-to-end data science projects and developing methodologies that advanced Nielsen’s digital ad and content rating products. His expertise in media measurement and data science drove the creation of innovative solutions.Recently, Abdelaziz transitioned to the public sector, joining the State of California's Department of Health Care Access and Information (HCAI). In his new role, he leverages his coding and data science leadership skills to make a meaningful impact, supporting HCAI’s mission to ensure quality, equitable, and affordable health care for all Californians.Abdelaziz is also the author of Distributed Machine Learning with PySpark: Migrating Effortlessly from Pandas and Scikit-Learn (Apress).Chapter 1: Overview of Scalable Deep Learning Pipelines on AWS.- Chapter 2: Setting Up a Deep Learning Environment on AWS.- Chapter 3: Data Preparation with PySpark for Deep Learning.- Chapter 4: Deep Learning with PyTorch for Regression.- Chapter 5: Deep Learning with TensorFlow for Regression.- Chapter 6: Deep Learning with PyTorch for Classification.- Chapter 7: Deep Learning with TensorFlow for Classification.- Chapter 8: Scalable Deep Learning Pipelines with Apache Airflow.- Chapter 9: Techniques for Improving Model Performance.- Chapter 10: Deploying and Monitoring Deep Learning Models.
Java For Dummies
LEARN TO CODE WITH JAVA AND OPEN THE GATE TO A REWARDING CAREERNow in its 9th edition, Java For Dummies gives you the essential tools you need to understand the programming language that 17 million software developers rely on. This beginner-friendly guide simplifies every step of the learning process. You'll learn the basics of Java and jump into writing your own programs. Along the way, you'll gain the skills you need to reuse existing code, create new objects, troubleshoot when things go wrong, and build working programs from the ground up. Java For Dummies will help you become a Java developer, even if you're brand new to the world of coding.* Learn the basic syntax and building blocks of Java* Begin to write your own programs in the latest Java version* Test out your code and problem-solve any errors you find* Discover techniques for writing code fasterThis is the must-have Dummies resource for beginning programmers and students who need a step-by-step guide to getting started with Java. You'll also love this book if you're a seasoned programmer adding another language to your repertoire. DR. BARRY BURD is a professor of Mathematics and Computer Science at Drew University in Madison, NJ. He’s a co-leader of the Garden State Java User Group and New York JavaSIG. In 2020, he was honored to be named a Java Champion. He’s the author of Beginning Programming with Java For Dummies and Flutter For Dummies.
IAPP CIPP / US Certified Information Privacy Professional Study Guide
PREPARE FOR SUCCESS ON THE IAPP CIPP/US EXAM AND FURTHER YOUR CAREER IN PRIVACY WITH THIS EFFECTIVE STUDY GUIDE - NOW INCLUDES A DOWNLOADABLE SUPPLEMENT TO GET YOU UP TO DATE ON THE CURRENT CIPP EXAM FOR 2024-2025!Information privacy has become a critical and central concern for small and large businesses across the United States. At the same time, the demand for talented professionals able to navigate the increasingly complex web of legislation and regulation regarding privacy continues to increase. Written from the ground up to prepare you for the United States version of the Certified Information Privacy Professional (CIPP) exam, Sybex's IAPP CIPP/US Certified Information Privacy Professional Study Guide also readies you for success in the rapidly growing privacy field. You'll efficiently and effectively prepare for the exam with online practice tests and flashcards as well as a digital glossary. The concise and easy-to-follow instruction contained in the IAPP/CIPP Study Guide covers every aspect of the CIPP/US exam, including the legal environment, regulatory enforcement, information management, private sector data collection, law enforcement and national security, workplace privacy and state privacy law, and international privacy regulation.* Provides the information you need to gain a unique and sought-after certification that allows you to fully understand the privacy framework in the US* Fully updated to prepare you to advise organizations on the current legal limits of public and private sector data collection and use* Includes 1 year free access to the Sybex online learning center, with chapter review questions, full-length practice exams, hundreds of electronic flashcards, and a glossary of key terms, all supported by Wiley's support agents who are available 24x7 via email or live chat to assist with access and login questionsPerfect for anyone considering a career in privacy or preparing to tackle the challenging IAPP CIPP exam as the next step to advance an existing privacy role, the IAPP CIPP/US Certified Information Privacy Professional Study Guide offers you an invaluable head start for success on the exam and in your career as an in-demand privacy professional. ABOUT THE AUTHORSMIKE CHAPPLE, PHD, CIPP/US, is Teaching Professor of Information Technology, Analytics, and Operations at Notre Dame’s Mendoza College of Business. He is the bestselling author of over 25 technical books. He is also the Academic Director of the University’s Master of Science in Business Analytics program. JOE SHELLEY, CIPP/US, is the Vice President for Libraries and Information Technology at Hamilton College in New York. He oversees the information security and privacy programs, IT risk management, business intelligence and analytics, and data governance. ContentsIntroduction xixAssessment Test xxixChapter 1 Privacy in the Modern Era 1Introduction to Privacy 2What Is Privacy? 3What Is Personal Information? 4What Isn’t Personal Information? 5Why Should We Care About Privacy? 7Generally Accepted Privacy Principles 8Management 9Notice 9Choice and Consent 10Collection 10Use, Retention, and Disposal 11Access 11Disclosure to Third Parties 12Security for Privacy 12Quality 14Monitoring and Enforcement 14Developing a Privacy Program 15Crafting Strategy, Goals, and Objectives 15Appointing a Privacy Official 16Privacy Roles 17Building Inventories 18Conducting a Privacy Assessment 18Implementing Privacy Controls 20Ongoing Operation and Monitoring 20Online Privacy 20Privacy Notices 21Privacy and Cybersecurity 21Cybersecurity Goals 22Relationship Between Privacy and Cybersecurity 23Privacy by Design 24Summary 25Exam Essentials 25Review Questions 27Chapter 2 Legal Environment 31Branches of Government 32Legislative Branch 32Executive Branch 33Judicial Branch 34Understanding Laws 36Sources of Law 36Analyzing a Law 41Legal Concepts 43Legal Liability 44Torts and Negligence 45Summary 46Exam Essentials 46Review Questions 48Chapter 3 Regulatory Enforcement 53Federal Regulatory Authorities 54Federal Trade Commission 54Federal Communications Commission 60Department of Commerce 61Department of Health and Human Services 61Banking Regulators 62Department of Education 63State Regulatory Authorities 63Self-Regulatory Programs 64Payment Card Industry 65Advertising 65Trust Marks 66Safe Harbors 66Summary 67Exam Essentials 68Review Questions 69Chapter 4 Information Management 73Data Governance 74Building a Data Inventory 74Data Classification 75Data Flow Mapping 77Data Lifecycle Management 78Workforce Training 79Cybersecurity Threats 80Threat Actors 81Incident Response 86Phases of Incident Response 86Preparation 87Detection and Analysis 88Containment, Eradication, and Recovery 88Post-incident Activity 88Building an Incident Response Plan 90Data Breach Notification 92Vendor Management 93Summary 94Exam Essentials 95Review Questions 97Chapter 5 Private Sector Data Collection 101FTC Privacy Protection 103General FTC Privacy Protection 103The Children’s Online Privacy Protection Act (COPPA) 104Future of Federal Enforcement 107Medical Privacy 110The Health Insurance Portability and AccountabilityAct (HIPAA) 111The Health Information Technology for Economic andClinical Health Act 119The 21st Century Cures Act 120Confidentiality of Substance Use Disorder PatientRecords Rule 121Financial Privacy 122Privacy in Credit Reporting 122Gramm–Leach–Bliley Act (GLBA) 125Red Flags Rule 129Consumer Financial Protection Bureau 130Educational Privacy 131Family Educational Rights and Privacy Act (FERPA) 131Telecommunications and Marketing Privacy 132Telephone Consumer Protection Act (TCPA) andTelemarketing Sales Rule (TSR) 133The Junk Fax Prevention Act (JFPA) 136Controlling the Assault of Non-solicited Pornographyand Marketing (CAN-SPAM) Act 136Telecommunications Act and Customer ProprietaryNetwork Information 138Cable Communications Policy Act 139Video Privacy Protection Act (VPPA) of 1988 140Driver’s Privacy Protection Act (DPPA) 141Digital Advertising and Data Ethics 142Web Scraping 143Summary 143Exam Essentials 144Review Questions 146Chapter 6 Government and Court Access to Private SectorInformation 151Law Enforcement and Privacy 152Access to Financial Data 153Access to Communications 157National Security and Privacy 162Foreign Intelligence Surveillance Act (FISA) of 1978 162FISA Amendments Act Section 702 164USA-PATRIOT Act 165The USA Freedom Act of 2015 167The Cybersecurity Information Sharing Act of 2015 168Civil Litigation and Privacy 169Compelled Disclosure of Media Information 170Electronic Discovery 171Summary 173Exam Essentials 173Review Questions 175Chapter 7 Workplace Privacy 179Introduction to Workplace Privacy 180Workplace Privacy Concepts 180U.S. Agencies Regulating Workplace Privacy Issues 181U.S. Antidiscrimination Laws 182Privacy Before, During, and After Employment 185Automated Employment Decision Tools 186Employee Background Screening 186Employee Monitoring 190Investigation of Employee Misconduct 194Termination of the Employment Relationship 196Summary 197Exam Essentials 198Review Questions 200Chapter 8 State Privacy Laws 205Federal vs. State Authority 206Elements of State Privacy Laws 207Applicability 207Data Subject Rights 208Privacy Notice Requirements 209Data Protection 209Enforcement 211Data Breach Notification 212Elements of State Data Breach Notification Laws 212Key Differences Among States 214Significant Developments 215Other Recent Updates to State Breach Notification Laws 218Comprehensive State Privacy Laws 220California Consumer Privacy Act (2018) andCalifornia Privacy Rights Act (2020) 220Virginia Consumer Data Protection Act 223Colorado Privacy Act 226Connecticut Data Privacy Act 229Utah 231Florida 232Oregon 234Texas 237Montana 239Subject-Specific State Privacy Laws 241Health and Genetic Information 241Online Privacy 243Biometric Information Privacy Regulations 247AI and Automated Decision-Making 249Data Brokers 250Financial Privacy 251California Financial Information Privacy Act 252Recent Developments 253Marketing Laws 254Summary 255Exam Essentials 256Review Questions 258Chapter 9 International Privacy Regulation 263International Data Transfers 264European Union General Data Protection Regulation 265Adequacy Decisions 268Binding Corporate Rules 272Standard Contractual Clauses 273Other Approved Transfer Mechanisms 273APEC Privacy Framework 274Cross-Border Enforcement Issues 276Global Privacy Enforcement Network 276Resolving Multinational Compliance Conflicts 276Summary 277Exam Essentials 277Review Questions 279Appendix Answers to Review Questions 283Chapter 1: Privacy in the Modern Era 284Chapter 2: Legal Environment 285Chapter 3: Regulatory Enforcement 287Chapter 4: Information Management 289Chapter 5: Private Sector Data Collection 291Chapter 6: Government and Court Access to Private SectorInformation 293Chapter 7: Workplace Privacy 294Chapter 8: State Privacy Laws 296Chapter 9: International Privacy Regulation 298Index 301
ChatGPT - Das Praxisbuch
Prompts, Texten, Coden, Schlagwörter: mit vielen Praxisbeispielen KI perfekt nutzen - für Einsteiger und Profi geeignet. In Erstauflage von Markt+Technik aus Dezember 2024.Die rasante Entwicklung der KI eröffnet ständig neue Möglichkeiten und Anwendungsbereiche. In ihrem aktuellen Handbuch entführen Oliver Bock und Florian Knust die Leser in die spannende Welt von ChatGPT. Sie beleuchten aktuelle Trends und Innovationen und geben einen umfassenden Einblick in die Funktionen sowie die vielseitigen Einsatzmöglichkeiten von ChatGPT. Dieses Buch ist unverzichtbar für alle, die das Potenzial von ChatGPT vollständig ausschöpfen möchten. Mit leicht nachvollziehbaren Schritt-für-Schritt-Anleitungen und praktischen Beispielen bringen die Autoren auch Einsteigern die komplexen Themen näher. Der praxisorientierte Teil präsentiert verschiedene Anwendungsszenarien und zeigt, wie ChatGPT nahtlos in den Alltag integriert werden kann.Aus dem Inhalt: ChatGPT leicht gemacht: Alles Wichtige für den schnellen Einstieg. Anwendungsbeispiele: 15 praktische Ideen für den direkten Einsatz im Alltag. Erweiterte Funktionen: Profi-Tipps und Techniken für fortgeschrittene Anwender. KI-Bildgenerierung mit DALL-E: Bilder erstellen und erkennen durch künstliche Intelligenz. Bilderkennung: Die oft übersehene Stärke von ChatGPT im Detail erklärt. CustomGPT: Dein individuelles ChatGPT einrichten und optimal nutzen. Gemeinsam mit KI arbeiten: ChatGPT, DALL-E und Midjourney effektiv kombinieren. Exklusive Vorteile: KI-Updates per E-Mail und Zugang zur kostenlosen KI-Community für Buchleser. Bonus: 50 getestete Power-Prompts für Texte, Social Media, Marketing, Schule und mehr
Natural Language Processing on Oracle Cloud Infrastructure
This book demonstrates how to use Oracle Cloud Infrastructure (OCI) and Hugging Face technologies to develop advanced NLP solutions. Through a practical case study, it addresses common NLP challenges and offers strategies for creating efficient, cost-effective transformer-based models. By the end of this book, you will have the skills and knowledge to create cutting-edge NLP solutions on OCI, customized to meet the needs of various industries and projects.The book takes you through the complete NLP solution life cycle—covering data preparation, model fine-tuning, deployment, and monitoring—while highlighting key topics such as cost-effectiveness and responsible AI for NLP implementations. Drawing from real-world experience and offering practical insights, it bridges the gap between theory and practice, equipping you to design and deploy scalable, cost-efficient NLP solutions.WHAT YOU WILL LEARN* Master key NLP concepts and the OCI ecosystem* Create high-quality datasets using Hugging Face and OCI Data Labeling Service* Fine-tune domain-specific pre-trained models from Hugging Face using OCI Data Science Notebook Sessions* Deploy and operationalize your models with OCI Data Science Model Deployments* Automate the NLP life cycle with OCI Data Science Pipelines* Implement cost-effective strategies throughout the entire NLP life cycle, from dataset preparation to model training and deploymentWHO THIS BOOK IS FORA diverse audience interested in implementing NLP solutions on Oracle Cloud Infrastructure: NLP practitioners, data scientists, and machine learning engineers who want to learn how to leverage Oracle AI and Hugging Face to implement an end-to-end NLP solution life cycle, from data preparation to model deployment; Oracle practitioners who want to expand their Oracle expertise by exploring OCI's advanced capabilities for building and scaling cutting-edge NLP solutions in enterprise environments; business decision makers who want to discover the strategic benefits of NLP solutions on OCI, including cost-effectiveness and responsible AI, while driving business valueHICHAM ASSOUDI is an accomplished IT professional and AI expert with over 30 years of experience, including more than 25 years specializing in Oracle technologies. He holds a PhD in Computer Science and is also an OCI Certified Architect. Hicham has held key roles such as Technology Manager at Oracle and IT Architect at IBM, offering highly specialized technical consulting to major corporations across Canada, the US, and Europe.Hicham’s journey into AI began over a decade ago during his doctoral studies, where he initially focused on intelligent agents and general machine learning. He later specialized in natural language processing (NLP) from the early days of transformer models, positioning him at the forefront of NLP innovation. As the founder of Typica.ai, an AI startup, Hicham applies cutting-edge research to practical NLP solutions, empowering organizations to leverage NLP for significant business impact.In addition to his industry contributions, Hicham maintains strong ties to academia as an External Research Associate at the AI Lab of UQAM University in Montreal, bridging the gap between academic research and real-world applications.Part 1: Foundations and Case Study Introduction.- Chapter 1: NLP Essentials.- Chapter 2: Oracle Cloud for NLP.- Chapter 3: Healthcare NLP Case Study.- Part2: Case Study Implementation.- Chapter 4: Tenancy Preparation.- Chapter 5: Dataset Preparation.- Chapter 6: Model Fine-tuning.- Part 3: Case Study Deployment and Wrap-Up.- Chapter 7: Model Deployment and Monitoring.- Chapter 8: MLOps and Conclusion.
Windows 11 For Seniors For Dummies, 2nd Edition
THE TOP-SELLING WINDOWS BOOK FOR THE OLDER AND WISER CROWDWindows 11 For Seniors For Dummies, 2nd Edition delivers fluff-free information on making the latest version of Windows work for you. You'll get clear guidance on the basics, troubleshooting tips, and advice for staying safe while you use Windows to get online. Even if you've never used Windows before, this friendly guide will quickly teach you how to get started, without all the jargon and complicated steps. These simple steps and solutions give you the confidence boost you need to navigate the latest interface and even try out the artificial intelligence tools built into Windows. With larger print and clearer graphics, this For Seniors title saves you time and energy as you learn your way around your Windows computer.* Get started with the latest version of Windows—without a lot of unnecessary jargon* Communicate with friends, keep track of files, share photos and videos, and stream your favorite media* Try out Copilot, the Windows AI tool that offers fast answers to any question* Be your own tech guru with step-by-step troubleshooting and maintenance adviceThese days, a new computer or a new Windows update shouldn't have to slow you down. Spend less time learning and more time doing, with this edition of Windows For Seniors For Dummies.CURT SIMMONS is an experienced tech educator who has published on a wide variety of topics, including Microsoft Windows, photo editing apps, networking, and mobile devices. He is also creator of the “Intro to Windows” course at ed2go.com and author of Drone Piloting For Dummies.
AI Solutions for the United Nations Sustainable Development Goals (UN SDGs)
Learn the United Nations Sustainable Development Goals (UN SDGs) and see how machine learning can significantly contribute to their realization. This book imparts both theoretical knowledge and hands-on experience in comprehending and constructing machine learning-based applications for addressing multiple UN SDGs using JavaScript. The reading begins with a delineation of diverse UN SDG targets, providing an overview of previous successful applications of machine learning in solving realistic problems aligned with these targets. It thoroughly explains fundamental concepts of machine learning algorithms for prediction and classification, coupled with their implementation in JavaScript and HTML programming. Detailed case studies examine challenges related to renewable energy, agriculture, food production, health, environment, climate change, water quality, air quality, and telecommunications, corresponding to various UN SDGs. Each case study includes related works, datasets, machine learning algorithms, programming concepts, and comprehensive explanations of JavaScript and HTML codes used for web-based machine learning applications. The results obtained are meticulously analyzed and discussed, showcasing the pivotal role of machine learning in advancing the relevant SDGs. By the end of this book, you’ll have a firm understanding of SDG fundamentals and the practical application of machine learning to address diverse challenges associated with these goals. You will: * Understand the fundamental concepts of the UN SDGs, AI, and machine learning algorithms. * Employ the correct machine learning algorithms to address challenges on the United Nations Sustainable Development Goals (UN SDGs)? * Develop web-based machine learning applications for the UN SDGs using Javascript, and HTML. * Analyze the impact of a machine learning-based solution on a specific UN SDG. Learn the United Nations Sustainable Development Goals (UN SDGs) and see how machine learning can significantly contribute to their realization. This book imparts both theoretical knowledge and hands-on experience in comprehending and constructing machine learning-based applications for addressing multiple UN SDGs using JavaScript. The reading begins with a delineation of diverse UN SDG targets, providing an overview of previous successful applications of machine learning in solving realistic problems aligned with these targets. It thoroughly explains fundamental concepts of machine learning algorithms for prediction and classification, coupled with their implementation in JavaScript and HTML programming. Detailed case studies examine challenges related to renewable energy, agriculture, food production, health, environment, climate change, water quality, air quality, and telecommunications, corresponding to various UN SDGs. Each case study includes related works, datasets, machine learning algorithms, programming concepts, and comprehensive explanations of JavaScript and HTML codes used for web-based machine learning applications. The results obtained are meticulously analyzed and discussed, showcasing the pivotal role of machine learning in advancing the relevant SDGs. By the end of this book, you’ll have a firm understanding of SDG fundamentals and the practical application of machine learning to address diverse challenges associated with these goals. What You’ll Learn * Understand the fundamental concepts of the UN SDGs, AI, and machine learning algorithms. * Employ the correct machine learning algorithms to address challenges on the United Nations Sustainable Development Goals (UN SDGs)? * Develop web-based machine learning applications for the UN SDGs using Javascript, and HTML. * Analyze the impact of a machine learning-based solution on a specific UN SDG. Who This Book Is For Data scientists, machine learning engineers, software professionals, researchers, and graduate students. Dr. Tulsi Pawan Fowdur received his BEng (Hons) degree in Electronic and Communication Engineering with honors from the University of Mauritius in 2004. He was also the recipient of a Gold medal for having produced the best degree project at the Faculty of Engineering in 2004. In 2005 he obtained a full-time PhD scholarship from the Tertiary Education Commission of Mauritius and was awarded his PhD degree in Electrical and Electronic Engineering in 2010 by the University of Mauritius. He is also a Registered Chartered Engineer of the Engineering Council of the UK, Fellow of the Institute of Telecommunications Professionals of the UK, and a Senior Member of the IEEE. He joined the University of Mauritius as an academic in June 2009 and is presently an Associate Professor at the Department of Electrical and Electronic Engineering of the University of Mauritius. His research interests include Mobile and Wireless Communications, Multimedia Communications, Networking and Security, Telecommunications Applications Development, the Internet of Things, and AI. He has published several papers in these areas and is actively involved in research supervision, reviewing papers, and also organizing international conferences. Lavesh Babooram received his BEng (Hons) degree in Telecommunications Engineering with Networking with honors from the University of Mauritius in 2021. He was also awarded a Gold medal for having produced the best degree project at the Faculty of Engineering in 2021. Since 2022, he has been an MSc by Applied Research student at the University of Mauritius. With in-depth knowledge of telecommunications applications design, analytics, and network infrastructure, he aims to pursue research in Networking, Multimedia Communications, Internet of Things, Artificial Intelligence, and Mobile and Wireless Communications. He joined Mauritius Telecom in 2022 and is currently working in the Customer Experience and Service Department as a Pre-Registration Trainee Engineer. Chapter 1: Introduction to Machine Learning Applications Development and the UN SDGs.- Chapter 2: Utilizing Machine Learning Algorithms for Power generation prediction and classification in Wind Farms.- Chapter 3: Crop Recommendation System Using Machine Learning Algorithms for achieving SDGs 2, 9, and 12.- Chapter 4: Aligning Manufacturing Emissions with SDGs 9 and 13 Using Machine Learning Algorithms.- Chapter 5: Water Potability Testing Using Machine Learning.- Applying Machine Learning for Air Quality Monitoring Targeting SDG 3 and 13.- Chapter 7: Clustering the Development of Worldwide Internet Connectivity with Unsupervised Learning for SDGs 7, 9, and 11.
Architecting Enterprise AI Applications
This book explores how to define, design, and maintain enterprise AI applications, exploring the impacts they will have on the teams who work with them.The book is structured into four parts. In Part 1: Defining Your AI Application, you are introduced to the dynamic interplay between human adaptability and AI specialization, the concept of meta systems, and the mechanics of prediction machines. In Part 2: Designing Your AI Application, the book delves into the anatomy of an AI application, unraveling the intricate relationships among data, machine learning, and reasoners. This section introduces the building blocks and enterprise architectural framework for designing multi-agent systems. Part 3: Maintaining Your AI Application takes a closer look at the ongoing life cycle of AI systems. You are guided through the crucial aspects of testing and test automation, providing a solid foundation for effective development practices. This section covers the critical tasks of security and information curation that ensure the long-term success of enterprise AI applications. The concluding section, Part 4: AI Enabled Teams, navigates the evolving landscape of collaborative efforts between humans and AI. It explores the impact of AI on remote work dynamics and introduces the new roles of the expert persona and the AI handler. This section concludes with a deep dive into the legal and ethical dimensions that AI-enabled teams must navigate.This book is a comprehensive guide that not only equips developers, architects, and product owners with the technical know-how of AI application development, but also delves into the broader implications for teams and society.WHAT YOU WILL LEARN* Understand the algorithms and processes that enable AI to make accurate predictions and enhance decision making* Grasp the concept of metasystems and their role in the design phase of AI applications* Know how data, machine learning, and reasoners drive the functionality and decision-making capabilities of AI applications* Know the architectural components necessary for scalable and maintainable multi-agent AI applications* Understand methodologies for testing AI applications, ensuring their robustness, accuracy, and reliability in real-world applications* Understand the evolving dynamics of human-AI coordination facing teams in the new enterprise working environmentWHO THIS BOOK IS FORA diverse audience, primarily targeting enterprise architects, middle managers, tech leads, and team leads entrenched in the IT sector or possessing a tech-savvy background, including professionals such as digital marketers. Additionally, tech-savvy individual contributors—ranging from digital content creators and data analysts to administrators and programmers—stand to benefit significantly.ANTON CAGLE is a seasoned leader specializing in cloud automation and AI Ops, boasting over two decades of expertise in enterprise architecture and application design. With a passion for delivering democratized, data-driven solutions and automation, Anton focuses on empowering medium to large-sized companies. His dedication extends to mentoring and coaching engineers at all skill levels, fostering a culture of continuous learning and innovation.Recognizing the pivotal role of cloud, data, and AI in shaping the future of business software, Anton is on a mission to guide companies beyond basic automation solutions. His goal is to seamlessly integrate big data and machine learning into organizational frameworks, preparing businesses for the next wave of scalable operations. Anton's approach has led to remarkable transformations for clients, including the reduction of deployment process waste, accelerated feature time to market, and the implementation of cutting-edge cloud data architectures.AHMED CEIFELNASR AHMED is a highly skilled ML engineer, data scientist, and cloud engineer with over six years of experience in developing and deploying data-driven solutions. Ahmed specializes in building and fine-tuning machine learning models, leveraging advanced deep learning techniques, and optimizing cloud-based solutions. His expertise extends to cloud engineering and DevOps practices, where he excels in designing and implementing scalable, efficient cloud architectures and automating deployment processes.With hands-on experience in AWS Cloud environments and a strong background in cloud tools, Ahmed is adept at integrating AI with cloud technologies to create robust, production-ready solutions. He has a proven track record of driving impactful results across various industries, from retail and real estate to fitness and enterprise applications.Ahmed is committed to continuous learning and growth, always seeking to make a significant impact in the fields of AI, data science, and cloud engineering. His career reflects his dedication to advancing technology, optimizing cloud infrastructure, and fostering innovation through data-driven strategies and cutting-edge technology.Part 1: Defining Your AI Application.- Chapter 1: Human Flexibility and AI Specialization.- Chapter 2: Meta Systems.- Chapter 3: Prediction Machines.- Part 2: Designing Your AI Application.- Chapter 4: Anatomy of an AI Application.- Chapter 5: Data, Machine Learning, and Reasoners.- Chapter 6: Large Language Models (LLMs).- Chapter 7: AI Agents.- Part 3: Maintaining Your AI Application.- Chapter 8: Testing Your Enterprise AI Application.- Chapter 9: Testing automation for enterprise ai applications.- Chapter 10: Security.- Chapter 11: Information Curation.- Part 4: AI Enabled Teams.- Chapter 12: Remote Work and Reskilling.- Chapter 13: Expert Personas.- Chapter 14: The Role of the AI Handler.- Chapter 15: Legal and Ethical Considerations.
SQL Schnelleinstieg
Datenbanken abfragen und verwalten in 14 TagenMit diesem Buch gelingt Ihnen der einfache Einstieg in das Datenbankmanagement mit der Abfragesprache SQL. Alle Grundlagen werden in 14 Kapiteln leicht verständlich anhand von Beispielen erläutert.Der Autor führt Sie Schritt für Schritt in den Einsatz von SQL und die Grundlagen relationaler Datenbanken ein: von der fundamentalen Syntax und den ersten Datenbankabfragen über das Verknüpfen von Tabellen bis hin zur Datenbankerstellung und der Zugriffskontrolle.Alle Beispiele beziehen sich auf eine Beispieldatenbank, die auf der Webseite des Verlags zum Download bereitsteht, und lassen sich leicht auf eigene Anwendungsfälle übertragen. Die Besonderheiten bei der Verwendung von PostgreSQL und MySQL werden bei jedem Beispiel beschrieben.So sind Sie perfekt auf den Einsatz von SQL im professionellen Umfeld vorbereitet.Aus dem Inhalt:Alle Grundlagen einfach erläutertSQL-Syntax und Datenbank-AbfragenFiltern mit BedingungenGruppierung von Daten und AggregatfunktionenVerknüpfen von Tabellen und ErgebnissenSkalarfunktionen und UnterabfragenDatenbanken erstellen und anpassenRechteverwaltung und ZugriffskontrolleKomplexe SQL-Konzepte – Trigger, Indizes und ViewsLeseprobe (PDF-Link)Über den Autor:Erik Schönwälder arbeitet als wissenschaftlicher Mitarbeiter (Doktorand) an der Technischen Universität Dresden am Lehrstuhl für Datenbanken. Als Dozent lehrt er hauptsächlich Themen wie Datenbank-Engineering, Information Retrieval, SQL und NoSQL. Auch außerhalb der Universität unterrichtet er seine Fachgebiete online, beispielsweise bei der Heise Academy oder auf Udemy.
Erstellung hochwertiger Shader für Unity®
Shader gelten oft als mystisch und schwer zu entwickeln, selbst für erfahrene Programmierer, Künstler und Entwickler aus anderen Bereichen des Spieldesigns. Dieses Buch räumt mit dieser Vorstellung auf, indem es Ihr Wissen über in Stufen aufbaut. Es beginnt mit grundlegenden Shader-Mathematiken, erklärt, wie sich die Denkweise der Shader-Entwicklung von anderen Arten von Kunst und Programmierung unterscheidet, und geht dann langsam auf Themen wie Vertex- und Fragment-Shader, Beleuchtung, Tiefenbasierte Effekte, Texture Mapping und Shader Graph ein.Jedes dieser Themen wird mit einer umfassenden Aufschlüsselung, der benötigten Theorie und einigen praktischen Anwendungen für die im jeweiligen Kapitel gelernten Techniken präsentiert. Der HLSL (High Level Shading Language)-Code und Shader Graphs werden für jeden relevanten Abschnitt bereitgestellt, ebenso wie zahlreiche Screenshots.Am Ende des Buches werden Sie ein gutes Verständnis für den Shader-Entwicklungsprozess haben und bestens gerüstet sein, um Ihre eigenen ästhetischen und leistungsstarken Shader-Effekte für Ihre Spiele zu erstellen!WAS SIE IN DIESEM BUCH LERNEN Shaders in den Rendering-Pipelines von Unity zu verwenden Shader zu schreiben und ihr Verhalten mit C#-Skripting zu ändern Shader Graph für eine Entwicklung ohne Code zu nutzen Die wichtige Mathematik hinter Shadern zu verstehen, insbesondere Raumtransformationen Die Leistung von Shadern zu analysieren, um Optimierungspotenziale zu identifizieren ZUM INHALT Kapitel 1: Einführung in Shader in Unity. Kapitel 2: Mathematik für die Shader-Entwicklung. Kapitel 3: Ihr allererster Shader. Kapitel 4: Shader-Grafik. Kapitel 5: Texturen, UV-Koordinaten & Normal Mapping. Kapitel 6: Transparenz. Kapitel 7: Der Tiefenpuffer. Kapitel 8: Transparenz und Alpha. Kapitel 9: Weitere Shader-Grundlagen. Kapitel 10: Beleuchtung und Schatten. Kapitel 11: Bildeffekte und Nachbearbeitung. Kapitel 12: Erweiterte Shader. Kapitel 13: Profiling und Optimierung. Kapitel 14: Shader-Rezepte für Ihre Spiele. ZIELGRUPPENDieses Buch richtet sich an Anfänger in der Shader-Entwicklung oder Leser, die den Schritt von Shader-Code zum Shader Graph machen möchten. Es enthält auch einen Abschnitt über Shader-Beispiele für diejenigen, die bereits die Grundlagen von Shadern kennen und nach spezifischen Anwendungsfällen suchen.DANIEL ILETT ist Doktorand an der University of Warwick. Als leidenschaftlicher Spieleentwickler hat er sich auf Shader und technische Kunst spezialisiert. Er ist Autor verschiedener Lehr- und Tutorial-Inhalte, darunter Videos und schriftliche Arbeiten, die sich an Anfänger und fortgeschrittene Entwickler richten. Darüber hinaus arbeitet er freiberuflich an Shadern und visuellen Effekten für Spiele.
Ökonomische Nachhaltigkeit - Interdisziplinäre Perspektiven
Dieses Buch bietet als Band 4 einer zunächst vier Bände umfassenden Reihe grundlegende Informationen zum Thema „Ökonomische Nachhaltigkeit“. Die weiteren Bände der Reihe sind Band 1 (Allgemeine Grundlagen), Band 2 (Ökologie) und Band 3 (Soziales). Band 4 erläutert nach einer Darstellung der Grundlagen der Wirtschaft folgende Themenbereiche: Wirtschaftssystem, Finanzierung, Infrastruktur, Produktion und Konsum, Handel sowie Arbeit. In jedem dieser Kapitel werden zunächst die wesentlichen Fakten dargestellt und darauf aufbauend die Herausforderungen und aktuellen Entwicklungen erörtert. Das Kapitel „Wirtschaftssystem“ behandelt unter anderem die Themen Postwachstumsökonomie und Gemeinwohl-Ökonomie, Unterschiede im Wohlstand in verschiedenen Ländern sowie die Grenzen des Wirtschaftswachstums. Im Kapitel „Finanzierung“ geht es beispielsweise um Besteuerung, Entwicklungshilfe und Auslandsverschuldung. Das Kapitel „Infrastruktur“ behandelt nach einer Erläuterung der Bedeutung wirtschaftlicher Infrastruktur exemplarisch die Themen Infrastrukturdefizite und nachhaltige Innovationen. Wandel des Konsumverhaltens, Ressourcenknappheit, Megatrends im Handel, globaler Handel, Zukunft der Arbeit sowie informeller Arbeitssektor sind ausgewählte Stichworte in den Kapiteln „Produktion und Konsum“, „Handel“ sowie „Arbeit“. Das Buch unterstützt Führungskräfte, Spezialisten in Unternehmen und Politik sowie Studierende dabei, die vielfältigen Herausforderungen der ökonomischen Nachhaltigkeit besser zu verstehen. Neben Ökonomen werden auch Informatiker, Juristen und andere Berufsgruppen angesprochen, die über ihre Fachperspektive hinaus ein umfassendes Verständnis von ökonomischer Nachhaltigkeit erwerben möchten. Prof. Dr. Michael Jacob lehrt und forscht im Fachbereich Betriebswirtschaft der Hochschule Kaiserslautern. Nach einer Bankausbildung und einem Studium der Betriebswirtschaftslehre war er unter anderem als Mitglied der Geschäftsführung bei PricewaterhouseCoopers Consulting S.à r.l. Luxembourg und als wissenschaftlicher Leiter am Institut für Betriebswirtschaft und Wirtschaftsinformatik tätig. Als Autor von bisher sieben Fachbüchern und vielen anderen Veröffentlichungen versucht er, die Theorie mit seinen umfangreichen Praxiserfahrungen zu verknüpfen und Themen fachübergreifend zu vernetzen.Grundlagen der ökonomischen Dimension.- Wirtschaftssystem.- Finanzierung.- Infrastruktur.- Produktion und Konsum.- Handel.- Arbeit.- Gesamtbetrachtung.