Microsoft SQL Server 2012 Administration. Real-World Skills for MCSA Certification and Beyond (Exams 70-461, 70-462, and 70-463)

This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology. While the first four chapters develop the linguistic and conceptual aspects of argument expression, the last four are devoted to their application to argument mining. These chapters investigate the facets of argument annotation, as well as argument mining system architectures and evaluation. How annotations may be used to develop linguistic data and how to train learning algorithms is outlined. A simple implementation is then proposed. The book ends with an analysis of non-verbal argumentative discourse. Argument Mining is an introductory book for engineers or students of linguistics, artificial intelligence and natural language processing. Most, if not all, the concepts of argumentation crucial for argument mining are carefully introduced and illustrated in a simple manner.

Your logical, linear guide to the fundamentals of data science programming Data science is exploding—in a good way—with a forecast of 1. 7 megabytes of new information created every second for each human being on the planet by 2020 and 11. 5 million job openings by 2026. It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time. Get grounded: the ideal start for new data professionals What lies ahead: learn about specific areas that data is transforming Be meaningful: find out how to tell your data story See clearly: pick up the art of visualization Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life—and everyone else’s!

Unravel the mysteries of blockchains Blockchain technologies are disrupting some of the world’s biggest industries. Blockchain For Dummies provides a fast way to catch up with the essentials of this quickly evolving tech. Written by an author involved in founding and analyzing blockchain solutions, this book serves to help those who need to understand what a blockchain can do (and can't do). This revised edition walks you through how a blockchainsecurely records data across independent networks. It offers a tour of some of the world’s best-known blockchains, including those that power Bitcoin and other cryptocurrencies. It also provides a glance at how blockchain solutions are affecting the worlds of finance, supply chain management, insurance, and governments. Get a clear picture of what a blockchain can do Learn how blockchains rule cryptocurrency and smart contracts Discover current blockchains and how each of them work Test blockchain apps Blockchain has become the critical buzzword in the world of financial technology and transaction security – and now you can make sense of it with the help of this essential guide.

Organizations can make data science a repeatable, predictable tool, which business professionals use to get more value from their data Enterprise data and AI projects are often scattershot, underbaked, siloed, and not adaptable to predictable business changes. As a result, the vast majority fail. These expensive quagmires can be avoided, and this book explains precisely how.  Data science is emerging as a hands-on tool for not just data scientists, but business professionals as well. Managers, directors, IT leaders, and analysts must expand their use of data science capabilities for the organization to stay competitive. Smarter Data Science helps them achieve their enterprise-grade data projects and AI goals. It serves as a guide to building a robust and comprehensive information architecture program that enables sustainable and scalable AI deployments. When an organization manages its data effectively, its data science program becomes a fully scalable function that’s both prescriptive and repeatable. With an understanding of data science principles, practitioners are also empowered to lead their organizations in establishing and deploying viable AI. They employ the tools of machine learning, deep learning, and AI to extract greater value from data for the benefit of the enterprise. By following a ladder framework that promotes prescriptive capabilities, organizations can make data science accessible to a range of team members, democratizing data science throughout the organization. Companies that collect, organize, and analyze data can move forward to additional data science achievements: Improving time-to-value with infused AI models for common use cases Optimizing knowledge work and business processes Utilizing AI-based business intelligence and data visualization Establishing a data topology to support general or highly specialized needs Successfully completing AI projects in a predictable manner Coordinating the use of AI from any compute node. From inner edges to outer edges: cloud, fog, and mist computing When they climb the ladder presented in this book, businesspeople and data scientists alike will be able to improve and foster repeatable capabilities. They will have the knowledge to maximize their AI and data assets for the benefit of their organizations.

Get ahead of the curve—learn about big data on the blockchain Blockchain came to prominence as the disruptive technology that made cryptocurrencies work. Now, data pros are using blockchain technology for faster real-time analysis, better data security, and more accurate predictions. Blockchain Data Analytics For Dummies is your quick-start guide to harnessing the potential of blockchain. Inside this book, technologists, executives, and data managers will find information and inspiration to adopt blockchain as a big data tool. Blockchain expert Michael G. Solomon shares his insight on what the blockchain is and how this new tech is poised to disrupt data. Set your organization on the cutting edge of analytics, before your competitors get there! Learn how blockchain technologies work and how they can integrate with big data Discover the power and potential of blockchain analytics Establish data models and quickly mine for insights and results Create data visualizations from blockchain analysis Discover how blockchains are disrupting the data world with this exciting title in the trusted For Dummies line!