Databaser

The rise of the platform economy into statelike dominance over the lives of entrepreneurs, users, and workers.The early Internet was a lawless place, populated by scam artists who made buying or selling anything online risky business. Then Amazon, eBay, Upwork, and Apple established secure digital platforms for selling physical goods, crowdsourcing labor, and downloading apps. These tech giants have gone on to rule the Internet like autocrats. How did this happen? How did users and workers become the hapless subjects of online economic empires? The Internet was supposed to liberate us from powerful institutions. In Cloud Empires, digital economy expert Vili Lehdonvirta explores the rise of the platform economy into statelike dominance over our lives and proposes a new way forward.Digital platforms create new marketplaces and prosperity on the Internet, Lehdonvirta explains, but they are ruled by Silicon Valley despots with little or no accountability. Neither workers nor users can "e;vote with their feet"e; and find another platform because in most cases there isn't one. And yet using antitrust law and decentralization to rein in the big tech companies has proven difficult. Lehdonvirta tells the stories of pioneers who helped create-or resist-the new social order established by digital platform companies. The protagonists include the usual suspects-Amazon founder Jeff Bezos, Travis Kalanick of Uber, and Bitcoin's inventor Satoshi Nakamoto-as well as Kristy Milland, labor organizer of Amazon's Mechanical Turk, and GoFundMe, a crowdfunding platform that has emerged as an ersatz stand-in for the welfare state. Only if we understand digital platforms for what they are-institutions as powerful as the state-can we begin the work of democratizing them.

"The most trusted explainer of the most mind-boggling concepts pulls back the veil of mystery that has too long cloaked the most valuable building blocks of modern science. Sean Carroll, with his genius for making complex notions entertaining, presents in his uniquely lucid voice the fundamental ideas informing the modern physics of reality. Physics offers deep insights into the workings of the universe but those insights come in the form of equations that often look like gobbledygook. Sean Carroll shows that they are really like meaningful poems that can help us fly over sierras to discover a miraculous multidimensional landscape alive with radiant giants, warped space-time, and bewilderingly powerful forces. High school calculus is itself a centuries-old marvel as worthy of our gaze as the Mona Lisa. And it may come as a surprise the extent to which all our most cutting-edge ideas about black holes are built on the math calculus enables. No one else could so smoothly guide readers to grasping the very equation Einstein used to describe his theory of general relativity. In the tradition of the legendary Richard Feynman lectures presented sixty years ago, this book is an inspiring, dazzling introduction to a way of seeing that will resonate across cultural and generational boundaries for many years to come"--

Learn the latest version of ArcGIS Pro with the newest edition of this bestselling series. Getting to Know ArcGIS Pro 2.8 introduces the tools and functions of ArcGIS Pro, the powerful desktop GIS application. Geographic information system (GIS) software is making a huge impact in businesses and organizations with mapping and analytic capabilities.  Getting to Know ArcGIS Pro 2.8 uses practical project workflows to teach best practices to readers of all skill levels. Readers will explore data visualizations, build a geodatabase, discover 3D GIS, create maps for web and physical presentations, and more. With more than 300 full-color images, Getting to Know ArcGIS Pro 2.8 clarifies complicated processes such as developing a geoprocessing model, using Python to write a script tool, and creating space-time cubes for analysis. Throughout the book, short sidebars about real-world GIS scenarios in specific industries help readers understand how ArcGIS Pro can be applied widely to solve problems. At the end of each chapter, a summary and glossary help reinforce the skills learned.  This edition has been completely updated for use with ArcGIS Pro 2.8. Other updates include new chapters on ArcGIS Online and geocoding. The Getting to Know series has been teaching readers about GIS for more than 20 years. Ideal for students, self-learners, and professionals who want to learn the premier GIS desktop application, Getting to Know ArcGIS Pro 2.8 is a textbook and desk reference designed to show users how they can use ArcGIS Pro successfully on their own.

An introduction to the Python programming language and its most popular tools for scientists, engineers, students, and anyone who wants to use Python for research, simulations, and collaboration.Doing Science with Python introduces readers to the most popular coding tools for scientific research, such as Anaconda, Spyder, Jupyter Notebooks, and JupyterLab, as well as dozens of important Python libraries for working with data, including NumPy, matplotlib, and pandas. No prior programming experience is required! You'll be guided through setting up a professional coding environment, then get a crash course on programming with Python, and explore the many tools and libraries ideal for working with data, designing visualizations, simulating natural events, and more. In the book's applied projects, you'll use these tools to write programs that perform tasks like counting tree rings, creating an interactive science slideshow, and simulating the foraging patterns of animals.

'Mandatory reading. Not just for company founders and leaders, but for anyone wanting to succeed in our ever-changing world.' Keith FerrazziWhat separates the world's most successful entrepreneurs and business tycoons from the rest? It's not their superhuman intelligence. It's something more fundamental: they understand how to turn uncertainty to their advantage.We all know that the future is inherently unknowable, and yet we behave and plan as though it is. Once we truly understand the nature of uncertainty, though, we can take practical steps to make the most of the opportunities that come our way. In Mastering Uncertainty award-winning author Matt Watkinson and investor and entrepreneur Csaba Konkoly offer a masterclass on the workings of luck and probability. They show how to calculate when to make big bets and when to pull back. And they offer supremely practical advice on how we can improve our odds, whether through maximising our networks, learning how to read warning signs, or assessing where best to place our energies.The unforeseen always occurs. Mastering Uncertainty shows you how to prepare for it and make the best use of it.

An Unconventional Guide to Start Speaking a New Language TodayBenny Lewis is the creator of www.fluentin3months.com, the largest language learning blog in the world. His proven techniques break down language learning myths and replace them with practical "language hacks" that take advantage of the skills we already possess. Fluent in 3 Months provides everything you need to make learning a new language fast, intuitive, and fun.

The New York Times bestseller, which for 10 years has been a must-have for women in business, is now completely revised and updated. In this new edition, internationally recognized executive coach Lois P. Frankel reveals a distinctive set of behaviors-over 130 in all-that women learn in girlhood that ultimately sabotage them as adults. She teaches you how to eliminate these unconscious mistakes that could be holding you back and offers invaluable coaching tips that can easily be incorporated into your social and business skills.

Join the data-centric revolution and master the concepts, techniques, and algorithms shaping the future of AI and ML development, using PythonKey Features- Grasp the principles of data centricity and apply them to real-world scenarios- Gain experience with quality data collection, labeling, and synthetic data creation using Python- Develop essential skills for building reliable, responsible, and ethical machine learning solutions- Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionIn the rapidly advancing data-driven world where data quality is pivotal to the success of machine learning and artificial intelligence projects, this critically timed guide provides a rare, end-to-end overview of data-centric machine learning (DCML), along with hands-on applications of technical and non-technical approaches to generating deeper and more accurate datasets.This book will help you understand what data-centric ML/AI is and how it can help you to realize the potential of 'small data'. Delving into the building blocks of data-centric ML/AI, you'll explore the human aspects of data labeling, tackle ambiguity in labeling, and understand the role of synthetic data. From strategies to improve data collection to techniques for refining and augmenting datasets, you'll learn everything you need to elevate your data-centric practices. Through applied examples and insights for overcoming challenges, you'll get a roadmap for implementing data-centric ML/AI in diverse applications in Python.By the end of this book, you'll have developed a profound understanding of data-centric ML/AI and the proficiency to seamlessly integrate common data-centric approaches in the model development lifecycle to unlock the full potential of your machine learning projects by prioritizing data quality and reliability.What you will learn- Understand the impact of input data quality compared to model selection and tuning- Recognize the crucial role of subject-matter experts in effective model development- Implement data cleaning, labeling, and augmentation best practices- Explore common synthetic data generation techniques and their applications- Apply synthetic data generation techniques using common Python packages- Detect and mitigate bias in a dataset using best-practice techniques- Understand the importance of reliability, responsibility, and ethical considerations in ML/AIWho this book is forThis book is for data science professionals and machine learning enthusiasts looking to understand the concept of data-centricity, its benefits over a model-centric approach, and the practical application of a best-practice data-centric approach in their work. This book is also for other data professionals and senior leaders who want to explore the tools and techniques to improve data quality and create opportunities for small data ML/AI in their organizations.Table of Contents- Exploring Data-Centric Machine Learning- From Model-Centric to Data-Centric - ML's Evolution- Principles of Data-Centric ML- Data Labeling Is a Collaborative Process- Techniques for Data Cleaning- Techniques for Programmatic Labeling in Machine Learning- Using Synthetic Data in Data-Centric Machine Learning- Techniques for Identifying and Removing Bias- Dealing with Edge Cases and Rare Events in Machine Learning- Kick-Starting Your Journey in Data-Centric Machine Learning

Solve real-world data problems and create data-driven workflows for easy data movement and processing at scale with Azure Data FactoryKey Features:Learn how to load and transform data from various sources, both on-premises and on cloudUse Azure Data Factory's visual environment to build and manage hybrid ETL pipelinesDiscover how to prepare, transform, process, and enrich data to generate key insightsBook Description:This new edition of the Azure Data Factory Cookbook, fully updated to reflect ADS V2, will help you get up and running by showing you how to create and execute your first job in ADF.You'll learn how to branch and chain activities, create custom activities, and schedule pipelines, as well as discovering the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage.With practical recipes, you'll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premises infrastructure with cloud-native tools to get relevant business insights. As you advance, you'll be able to integrate the most commonly used Azure Services into ADF and understand how Azure services can be useful in designing ETL pipelines. You'll familiarize yourself with the common errors that you may encounter while working with ADF and find out how to use the Azure portal to monitor pipelines. You'll also understand error messages and resolve problems in connectors and data flows with the debugging capabilities of ADF.Two new chapters covering Azure Data Explorer and key best practices have been added, along with new recipes throughout.By the end of this book, you'll be able to use ADF as the main ETL and orchestration tool for your data warehouse or data platform projects.What You Will Learn:Create an orchestration and transformation job in ADFDevelop, execute, and monitor data flows using Azure SynapseCreate big data pipelines using Databricks and Delta tablesWork with big data in Azure Data Lake using Spark PoolMigrate on-premises SSIS jobs to ADFIntegrate ADF with commonly used Azure services such as Azure ML, Azure Logic Apps, and Azure FunctionsRun big data compute jobs within HDInsight and Azure DatabricksCopy data from AWS S3 and Google Cloud Storage to Azure Storage using ADF's built-in connectorsWho this book is for:This book is for ETL developers, data warehouse and ETL architects, software professionals, and anyone else who wants to learn about the common and not-so-common challenges faced while developing traditional and hybrid ETL solutions using Microsoft's Azure Data Factory. You'll also find this book useful if you are looking for recipes to improve or enhance your existing ETL pipelines. Basic knowledge of data warehousing is a prerequisite.

Unlock the full potential of your data by mastering the art of cleaning, preparing, and transforming data with Power BI for smarter insights and data visualizationsKey Features:Implement best practices for connecting, preparing, cleaning, and analyzing multiple sources of data using Power BIConduct exploratory data analysis (EDA) using DAX, PowerQuery, and the M languageApply your newfound knowledge to tackle common data challenges for visualizations in Power BIPurchase of the print or Kindle book includes a free PDF eBookBook Description:Microsoft Power BI offers a range of powerful data cleaning and preparation options through tools such as DAX, Power Query, and the M language. However, despite its user-friendly interface, mastering it can be challenging. Whether you're a seasoned analyst or a novice exploring the potential of Power BI, this comprehensive guide equips you with techniques to transform raw data into a reliable foundation for insightful analysis and visualization.This book serves as a comprehensive guide to data cleaning, starting with data quality, common data challenges, and best practices for handling data. You'll learn how to import and clean data with Query Editor and transform data using the M query language. As you advance, you'll explore Power BI's data modeling capabilities for efficient cleaning and establishing relationships. Later chapters cover best practices for using Power Automate for data cleaning and task automation. Finally, you'll discover how OpenAI and ChatGPT can make data cleaning in Power BI easier.By the end of the book, you will have a comprehensive understanding of data cleaning concepts, techniques, and how to use Power BI and its tools for effective data preparation.What You Will Learn:Connect to data sources using both import and DirectQuery optionsUse the Query Editor to apply data transformationsTransform your data using the M query languageDesign clean and optimized data models by creating relationships and DAX calculationsPerform exploratory data analysis using Power BIAddress the most common data challenges with best practicesExplore the benefits of using OpenAI, ChatGPT, and Microsoft Copilot for simplifying data cleaningWho this book is for:If you're a data analyst, business intelligence professional, business analyst, data scientist, or anyone who works with data on a regular basis, this book is for you. It's a useful resource for anyone who wants to gain a deeper understanding of data quality issues and best practices for data cleaning in Power BI. If you have a basic knowledge of BI tools and concepts, this book will help you advance your skills in Power BI.

Harness the power of Microsoft Fabric to develop data analytics solutions for various use cases guided by step-by-step instructionsKey FeaturesExplore Microsoft Fabric and its features through real-world examplesBuild data analytics solutions for lakehouses, data warehouses, real-time analytics, and data scienceMonitor, manage, and administer your Fabric platform and analytics system to ensure flexibility, performance, security, and controlPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionDiscover the capabilities of Microsoft Fabric, the premier unified solution designed for the AI era, seamlessly combining data integration, OneLake, transformation, visualization, universal security, and a unified business model. This book provides an overview of Microsoft Fabric, its components, and the wider analytics landscape.In this book, you'll explore workloads such as Data Factory, Synapse Data Engineering, data science, data warehouse, real-time analytics, and Power BI. You'll learn how to build end-to-end lakehouse and data warehouse solutions using the medallion architecture, unlock the real-time analytics, and implement machine learning and AI models. As you progress, you'll build expertise in monitoring workloads and administering Fabric across tenants, capacities, and workspaces. The book also guides you step by step through enhancing security and governance practices in Microsoft Fabric and implementing CI/CD workflows with Azure DevOps or GitHub. Finally, you'll discover the power of Copilot, an AI-driven assistant that accelerates your analytics journey.By the end of this book, you'll have unlocked the full potential of AI-driven data analytics, gaining a comprehensive understanding of the analytics landscape and mastery over the essential concepts and principles of Microsoft Fabric.What you will learnGet acquainted with the different services available in Microsoft FabricBuild end-to-end data analytics solution to scale and manage high performanceIntegrate data from different types of data sourcesApply transformation with Spark, Notebook, and T-SQLUnderstand and implement real-time stream processing and data science capabilitiesPerform end-to-end processes for building data analytics solutions in the AI eraDrive insights by leveraging Power BI for reporting and visualizationImprove productivity with AI assistance and Copilot integrationWho this book is forThis book is for data professionals, including data analysts, data engineers, data scientists, data warehouse developers, ETL developers, business analysts, AI/ML professionals, software developers, and Chief Data Officers who want to build a future-ready data analytics solution for long-term success in the AI era.For PySpark and SQL students entering the data analytics field, this book offers a broad foundation for developing the skills to build end-to-end analytics systems for various use cases. Basic knowledge of SQL and Spark is assumed.Table of ContentsOverview of Microsoft Fabric and Understanding Its Different ConceptsUnderstanding Different Workloads and Getting Started with Microsoft Fabric Building an End-to-End Analytics System - LakehouseBuilding an End-to-End Analytics System - Data WarehouseBuilding an End-to-End Analytics System - Real-Time AnalyticsBuilding an End-to-End Analytics System - Data ScienceMonitoring Overview and Monitoring Different WorkloadsAdministering FabricSecurity and Governance Overview(N.B. Please use the Look Inside option to see further chapters)

Critical Geography examines the power structures, inequality, and the dominant ideologies that shape physical space. By critically analyzing these forces, the publication stimulates conversations about social justice, environmental sustainability, and transformative change. The artistic practices featured in the book shed light on systemic oppression, violence, and pressing environmental issues, and encompass a wide range of image-based practices that make inequality visible in both colonial and postcolonial contexts, including mapping, social media, and technology. FOTOFEST is a Houston-based contemporary arts organization co-founded by photojournalists Frederick Baldwin and Wendy Watriss. The use of photography or related media to examine social, cultural, and political histories as well as contemporary life is central to FotoFest's mission. In addition to year-round programming, FotoFest organizes a city-wide biennial project that includes large-scale central exhibitions, curated lectures, performances, a symposium, and a film program.

Datenschutz und Informationsfreiheit gewinnen in der digitalen Gesellschaft dramatisch an Bedeutung. Die 8. Auflage der Einführung in das Datenschutzrecht zeigt, dass sich durch die aktuelle Entwicklung in der europäischen Rechtsprechung, Rechtspraxis und Gesetzgebung wichtige Veränderungen in Struktur und Strategie des Datenschutzes sowie der kommunikativen Freiheitsrechte ergeben haben. Im Fokus stehen die EU-Datenschutz-Grundverordnung (DS-GVO), die EU-Richtlinie für den Bereich Justiz und Inneres (DSRLJ) sowie einschlägige Gesetze auf nationaler Ebene wie das Telekommunikation-Telemedien-Datenschutz-Gesetz (TTDSG). Anhand von Fallbeispielen werden die rechtlichen Rahmenbedingungen erläutert und deren Auslegung durch Literatur und Rechtsprechung kritisch diskutiert. Aktuelle Herausforderungen für die Privatheit etwa durch Künstliche Intelligenz und Scoring oder die Rolle von Daten als Währung in der Datenökonomie werden datenschutzrechtlich unter die Lupe genommen. In einem eigenen Kapitel werden schließlich ausführlich die technischen und organisatorischen Maßnahmen zur Eindämmung von Risiken sowie zur Gewährleistung von Datenschutz und Datensicherheit sowie Informationsfreiheit vermittelt.

Troubleshoot query performance issues, identify anti-patterns in your code, and write efficient T-SQL queries with this guide for T-SQL developersKey Features:- A definitive guide to mastering the techniques of writing efficient T-SQL code- Learn query optimization fundamentals, query analysis, and how query structure impacts performance- Discover insightful solutions to detect, analyze, and tune query performance issues- Purchase of the print or Kindle book includes a free PDF eBookBook Description:Data professionals seeking to excel in Transact-SQL for Microsoft SQL Server and Azure SQL Database often lack comprehensive resources. Learn T-SQL Querying second edition focuses on indexing queries and crafting elegant T-SQL code enabling data professionals gain mastery in modern SQL Server versions (2022) and Azure SQL Database. The book covers new topics like logical statement processing flow, data access using indexes, and best practices for tuning T-SQL queries.Starting with query processing fundamentals, the book lays a foundation for writing performant T-SQL queries. You'll explore the mechanics of the Query Optimizer and Query Execution Plans, learning to analyze execution plans for insights into current performance and scalability. Using dynamic management views (DMVs) and dynamic management functions (DMFs), you'll build diagnostic queries. The book covers indexing and delves into SQL Server's built-in tools to expedite resolution of T-SQL query performance and scalability issues. Hands-on examples will guide you to avoid UDF pitfalls and understand features like predicate SARGability, Query Store, and Query Tuning Assistant.By the end of this book, you'll have developed the ability to identify query performance bottlenecks, recognize anti-patterns, and avoid pitfallsWhat You Will Learn:- Identify opportunities to write well-formed T-SQL statements- Familiarize yourself with the Cardinality Estimator for query optimization- Create efficient indexes for your existing workloads- Implement best practices for T-SQL querying- Explore Query Execution Dynamic Management Views- Utilize the latest performance optimization features in SQL Server 2017, 2019, and 2022- Safeguard query performance during upgrades to newer versions of SQL ServerWho this book is for:This book is for database administrators, database developers, data analysts, data scientists and T-SQL practitioners who want to master the art of writing efficient T-SQL code and troubleshooting query performance issues through practical examples. A basic understanding of T-SQL syntax, writing queries in SQL Server, and using the SQL Server Management Studio tool will be helpful to get started.Table of Contents- Understanding Query Processing- Mechanics of the Query Optimizer- Exploring Query Execution Plans- Indexing for T-SQL Performance- Writing Elegant T-SQL Queries- Discovering T-SQL Anti-patterns in Depth - Building diagnostic queries using DMVs and DMFs- Building XEvent profiler traces- Comparative analysis of Query Plans- Tracking performance history with Query Store- Troubleshooting Live Queries- Managing optimizer changes with the Query Tuning Assistant

Rise above the competition and excel in your next interview with this one-stop guide to Python, SQL, version control, statistics, machine learning, and much moreKey FeaturesAcquire highly sought-after skills of the trade, including Python, SQL, statistics, and machine learningGain the confidence to explain complex statistical, machine learning, and deep learning theoryExtend your expertise beyond model development with version control, shell scripting, and model deployment fundamentalsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe data science job market is saturated with professionals of all backgrounds, including academics, researchers, bootcampers, and Massive Open Online Course (MOOC) graduates. This poses a challenge for companies seeking the best person to fill their roles. At the heart of this selection process is the data science interview, a crucial juncture that determines the best fit for both the candidate and the company.Cracking the Data Science Interview provides expert guidance on approaching the interview process with full preparation and confidence. Starting with an introduction to the modern data science landscape, you'll find tips on job hunting, resume writing, and creating a top-notch portfolio. You'll then advance to topics such as Python, SQL databases, Git, and productivity with shell scripting and Bash. Building on this foundation, you'll delve into the fundamentals of statistics, laying the groundwork for pre-modeling concepts, machine learning, deep learning, and generative AI. The book concludes by offering insights into how best to prepare for the intensive data science interview.By the end of this interview guide, you'll have gained the confidence, business acumen, and technical skills required to distinguish yourself within this competitive landscape and land your next data science job.What you will learnExplore data science trends, job demands, and potential career pathsSecure interviews with industry-standard resume and portfolio tipsPractice data manipulation with Python and SQLLearn about supervised and unsupervised machine learning modelsMaster deep learning components such as backpropagation and activation functionsEnhance your productivity by implementing code versioning through GitStreamline workflows using shell scripting for increased efficiencyWho this book is forWhether you're a seasoned professional who needs to brush up on technical skills or a beginner looking to enter the dynamic data science industry, this book is for you. To get the most out of this book, basic knowledge of Python, SQL, and statistics is necessary. However, anyone familiar with other analytical languages, such as R, will also find value in this resource as it helps you revisit critical data science concepts like SQL, Git, statistics, and deep learning, guiding you to crack through data science interviews.Table of ContentsExploring the Modern Data Science LandscapeFinding a Job in Data ScienceProgramming with PythonVisualizing Data and Data StorytellingQuerying Databases with SQLScripting with Shell and Bash Commands in LinuxUsing Git for Version ControlMining Data with Probability and StatisticsUnderstanding Feature Engineering and Preparing Data for ModelingMastering Machine Learning ConceptsBuilding Networks with Deep LearningImplementing Machine Learning Solutions with MLOpsMastering the Interview RoundsNegotiating Compensation

Internet-of-Things (IoT) has enormous interest from the research community in smart applications due to its ability to link any electronic object to a network. The IoT networks are centered over the Wireless Sensor Networks (WSN) and hence the IoT networks suffer from batter constraint problems similar to WSN. In the first contribution, Fractional Firefly Algorithm (FFA) and Chicken Swarm Optimization (CSO) algorithms are used to develop the FFA+CSO based multipath routing protocol. This model utilizes FFA for the optimal selection of cluster heads and CSO for optimal routing path selection based on different routing network metrics such as energy, delay, link quality, lifetime and hop count. The second contribution analyzes the fault tolerance limitations of FA+CSO and FFA+CSO to develop Fractional Gaussian Firefly Algorithm (FGFA) and Darwinian Chicken Swarm Optimization (DCSO) algorithms were developed to form FGFA+DCSO based multipath routing protocol by improving the FFA and CSO to adapt the energy efficiency in CH selection and fault tolerance in optimal route selection.

This book is a comprehensive tribute to the Polish-Belgian artist Tapta (Maria Wierusz-Kowalska). Her work transcends traditional artistic boundaries, captivating audiences with her innovative exploration of fluid spaces and dynamic interactions. Her work, an important contribution to twentieth century sculpture, is essentially divided into two major sections: the textile works of the 1960s to 1980s and the subsequent neoprene works of the last years of her life. Her practice moved away from traditional weaving through experimental techniques and evolved into three-dimensional works-first made of cords, then of neoprene sheets-that interacted with the space and the viewer. TAPTA (*1926-1997) was born in Poland and came to Belgium as a political refugee with her husband, Krzysztof Wierusz-Kowalski, after taking part in the Warsaw Uprising of 1944. She studied weaving at the La Cambre National School of Visual Arts, Brussels, from where she graduated in 1949. Shortly afterwards, the couple moved to the Belgian Congo (now Democratic Republic of the Congo), where they lived from 1950 to 1960. On their return to Belgium in 1960, until her sudden death in 1997, she worked in Brussels as an artist and-from 1976 until 1990-as a professor at La Cambre.

Der Beschluss ist als Verfahren kollektiver Willensbildung im Privatrecht durchweg etabliert. Anders als die einzelne Willenserklärung oder der Vertrag hat er allerdings keine allgemeine Regelung erfahren. Der Autor weist nach, dass für privatrechtliche Beschlüsse stets die gleichen Funktionsvoraussetzungen gelten und diese daher auf einer einheitlichen Dogmatik basieren. Aufbauend hierauf arbeitet er diese Dogmatik heraus und ordnet die Entfaltung privaten Handelns in Beschlussform in generalisierender Weise. In der Gesamtschau entsteht ein Koordinatensystem, das als eine allgemeine Beschlusslehre ein strukturiertes Navigieren durch die Entscheidungsfindung im Kollektiv ermöglicht.

"Au-delà des Filtrages" est l'histoire captivante d'une relation contemporaine entre un jeune homme et une femme, qui explore les complexités de la communication numérique et des médias sociaux dans notre société moderne. Le livre plonge dans les challenges et les dilemmes auxquels ils sont confrontés dans leur vie amoureuse et met en lumière l'impact des filtres et des apparences trompeuses dans leurs interactions. Tout au long du récit, les personnages doivent apprendre à se connaître en dehors des écrans et à naviguer à travers les contraintes de la technologie pour trouver une connexion authentique. Cette petite brochure de 51 pages offre une réflexion profonde sur les liens humains à l'ère numérique et pose la question "Sommes-nous vraiment connectés ?".

Turn raw data into meaningful solutions¿DESCRIPTION Learn Data Science from Scratch equips you with the essential tools and techniques, from Python libraries to machine learning algorithms, to tackle real-world problems and make informed decisions.This book provides a thorough exploration of essential data science concepts, tools, and techniques. Starting with the fundamentals of data science, you will progress through data collection, web scraping, data exploration and visualization, and data cleaning and pre-processing. You will build the required foundation in statistics and probability before diving into machine learning algorithms, deep learning, natural language processing, recommender systems, and data storage systems. With hands-on examples and practical advice, each chapter offers valuable insights and key takeaways, empowering you to master the art of data-driven decision making.By the end of this book, you will be well-equipped with the essential skills and knowledge to navigate the exciting world of data science. You will be able to collect, analyze, and interpret data, build and evaluate machine learning models, and effectively communicate your findings, making you a valuable asset in any data-driven environment.WHAT YOU WILL LEARN¿ Master key data science tools like Python, NumPy, Pandas, and more.¿ Build a strong foundation in statistics and probability for data analysis.¿ Learn and apply machine learning, from regression to deep learning.¿ Expertise in NLP and recommender systems for advanced analytics.¿ End-to-end data project from data collection to model deployment, with planning and execution.WHO THIS BOOK IS FORThis book is ideal for beginners with a basic understanding of programming, particularly in Python, and a foundational knowledge of mathematics. It is well-suited for aspiring data scientists and analysts.

Introducing the "Data Warehousing: Optimizing Data Storage and Retrieval for Business Success" bundle!Unlock the full potential of your data with this comprehensive collection of four essential books:1. Data Warehousing Fundamentals: A Beginner's Guide· Dive into the foundational principles of data warehousing and learn how to build a solid framework for storing and managing your organization's data.· Understand the importance of data modeling and gain insights into the extraction, transformation, and loading (ETL) processes essential for efficient data management.2. Mastering Data Modeling for Data Warehousing· Take your data modeling skills to the next level with advanced techniques for conceptual, logical, and dimensional modeling.· Learn how to design scalable and efficient data warehouses that meet the evolving needs of your organization.3. Advanced ETL Techniques for Data Warehousing Optimization· Optimize your ETL processes and streamline data extraction, transformation, and loading for maximum efficiency.· Explore advanced techniques such as incremental loading and change data capture (CDC) to ensure the smooth operation of your data warehouse.4. Big Data Analytics: Harnessing the Power of Data Warehousing for Experts· Unlock the transformative potential of big data analytics and gain actionable insights to drive informed decision-making.· Discover how to leverage your data warehouse for real-time data processing, predictive modeling, and more.With this bundle, you'll gain the knowledge and skills needed to optimize your data storage and retrieval processes, empowering you to harness the power of data for business success. Whether you're a beginner looking to build a solid foundation or an expert seeking advanced strategies, this bundle has something for everyone. Don't miss out on this opportunity to revolutionize your approach to data warehousing and take your business to new heights!

This book provides a guide for those looking to understand the potential of blockchain technology and its impact on various industries. The book provides an in-depth exploration of blockchain technology, its use cases, and the opportunities and challenges it presents. From digital currencies and smart contracts to supply chain management and decentralized finance, the book covers all the key aspects of blockchain technology. The authors also go beyond the technical details, providing valuable insights and practical advice on how to navigate this new era of decentralization and trustless transactions. The book is an ideal read for researchers, entrepreneurs, investors, or anyone looking to stay ahead of the curve and stay informed about the future of blockchain technology.

The book presents original contributions to the theories and practices of emerging internet, data, and web technologies and their applicability in businesses, engineering, and academia. As a key feature, it addresses advances in the life-cycle exploitation of data generated from the digital ecosystem data technologies that create value for the knowledge and businesses toward a collective intelligence approach.Internet has become the most proliferative platform for emerging large-scale computing paradigms. Among these, data and web technologies are two most prominent paradigms, in a variety of forms such as data centers, cloud computing, mobile cloud, and mobile web services. These technologies altogether create a digital ecosystem whose corner stone is the data cycle, from capturing to processing, analysis, and visualization. The investigation of various research and development issues in this digital ecosystem is boosted by the ever-increasing needs of real-life applications, which are based on storing and processing large amounts of data. Researchers, software developers, practitioners, and students interested in the field of data and web technologies will find this book useful and a reference for their activity.