Leverage the power of the popular Jupyter notebooks to simplify your data science tasks without any hassle Key Features Create and share interactive documents with live code, text and visualizations Integrate popular programming languages such as Python, R, Julia, Scala with Jupyter Develop your widgets and interactive dashboards with these innovative recipes Book DescriptionJupyter has garnered a strong interest in the data science community of late, as it makes common data processing and analysis tasks much simpler. This book is for data science professionals who want to master various tasks related to Jupyter to create efficient, easy-to-share, scientific applications. The book starts with recipes on installing and running the Jupyter Notebook system on various platforms and configuring the various packages that can be used with it. You will then see how you can implement different programming languages and frameworks, such as Python, R, Julia, JavaScript, Scala, and Spark on your Jupyter Notebook. This book contains intuitive recipes on building interactive widgets to manipulate and visualize data in real time, sharing your code, creating a multi-user environment, and organizing your notebook. You will then get hands-on experience with Jupyter Labs, microservices, and deploying them on the web. By the end of this book, you will have taken your knowledge of Jupyter to the next level to perform all key tasks associated with it. What you will learn Install Jupyter and configure engines for Python, R, Scala and more Access and retrieve data on Jupyter Notebooks Create interactive visualizations and dashboards for different scenarios Convert and share your dynamic codes using HTML, JavaScript, Docker, and more Create custom user data interactions using various Jupyter widgets Manage user authentication and file permissions Interact with Big Data to perform numerical computing and statistical modeling Get familiar with Jupyter's next-gen user interface - JupyterLab Who this book is forThis cookbook is for data science professionals, developers, technical data analysts, and programmers who want to execute technical coding, visualize output, and do scientific computing in one tool. Prior understanding of data science concepts will be helpful, but not mandatory, to use this book.

Quantitative Intelligence Analysis describes the model-based method of intelligence analysis that represents the analyst's mental models of a subject, as well as the analyst's reasoning process exposing what the analyst believes about the subject, and how they arrived at those beliefs and converged on analytic judgments. It includes: *Specific methods of explicitly representing the analyst's mental models as computational models; *dynamic simulations and interactive analytic games; *the structure of an analyst's mental model and the theoretical basis for capturing and representing the tacit knowledge of these models explicitly as computational models detailed description of the use of these models in rigorous, structured analysis of difficult targets; *model illustrations and simulation descriptions; *the role of models in support of collection and operations; *case studies that illustrate a wide range of intelligence problems; *And a recommended curriculum for technical analysts.

Das Buch begleitet den UEbergang von der analogen zur digitalen Energiewirtschaft und gibt dem Leser wertvolle Impulse fur die Erschliessung neuer, lukrativer Betatigungsfelder. Autoren aus Wissenschaft und Praxis liefern ausgewahlte Antworten auf die enormen Herausforderungen angesichts von Digitalisierung und Dezentralisierung im Energiesektor. Insofern soll das Buch Mut machen, die digitale Transformation zugig anzugehen und den Veranderungsprozess insgesamt als Chance zu begreifen. Die Debatte um die Ausgestaltung und Zukunft von Utility 4.0 hat damit gerade erst begonnen.

Master Data Analytics Hands-On by Solving Fascinating Problems You'll Actually Enjoy! Harvard Business Review recently called data science "The Sexiest Job of the 21st Century." It's not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it's indispensable. Unfortunately, there's been nothing easy about learning data science-until now. Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell's Outliers: It teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything's software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you'll always know why you're doing what you're doing. You'll master data science by answering fascinating questions, such as: * Are religious individuals more or less likely to have extramarital affairs? * Do attractive professors get better teaching evaluations? * Does the higher price of cigarettes deter smoking? * What determines housing prices more: lot size or the number of bedrooms? * How do teenagers and older people differ in the way they use social media? * Who is more likely to use online dating services? * Why do some purchase iPhones and others Blackberry devices? * Does the presence of children influence a family's spending on alcohol? For each problem, you'll walk through defining your question and the answers you'll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon.

Wie wird eine Website erfolgreich - fur Unternehmen, Vereine, Verbande oder Privatpersonen? Mit leicht nachvollziehbaren Beispielen und erprobten Praxistipps erfahrt der Leser, wie er seine Website fur Suchmaschinen optimieren kann, die Bedienbarkeit verbessert und die Performance steigert, damit die Besucher der Website das Angebot gerne und intensiv nutzen. Die Planung eines Website-Relaunches wird ebenso detailliert dargestellt wie die Moeglichkeiten, den Webauftritt selber erfolgreich zu vermarkten.

Konzepte und Methoden des Lean Managements sind im Produktionsumfeld etabliert. Die administrativen Bereiche stehen hier vor dem Anfang Lean Office und somit Lean Thinking halt Einzug. Einen Baustein stellt hier das Lean Reporting dar. Neben den Grundlagen und Methoden des Lean Reportings werden praxisbezogene Szenarien zur Umsetzung aufgezeigt. Nutzbare Potentiale und Losungswege zur Realisierung eines modernen und effizienten Berichtswesens sind das Ergebnis.
Lean Reporting ist somit ein Thema das sowohl die Fachbereiche Controlling und Finanzen als auch die Informatik sowie das Management anspricht."

This is the first practical guide to using QSR NUD.IST - the leading software package for development, support and management of qualitative data analysis projects.

The book takes a user's perspective and presents the software as a set of tools for approaching a range of research issues and projects that the researcher may encounter. It starts by introducing and explaining what the software is intended to do and the different types of problems that it can be applied to. It then covers the key stages in carrying out qualitative data analysis, including strategies for setting up a project in QSR NUD.IST, and how to explore the data through coding, indexing and searching. There are practical exercises throughout to illustrate the strategies and techniques discussed.

QSR NUD·IST 4 is distributed by Scolari, Sage Publications Software.

The use of computers in qualitative research has redefined the way social researchers handle qualitative data. Two leading researchers in the field have written this lucid and accessible text on the principal approaches in qualitative research and show how the leading computer programs are used in computer-assisted qualitative data analysis (CAQDAS).

The authors examine the advantages and disadvantages of computer use, the impact of research resources and the research environment on the research process, and the status of qualitative research. They provide a framework for developing the craft and practice of CAQDAS and conclude by examining the latest techniques and their implications for the evolution of qualitative resear

With recent significant advances having been made in computer-aided methods to support qualitative data analysis, a whole new range of methodological questions arises: Will the software employed `take over' the analysis? Can computers be used to improve reliability and validity? Can computers make the research process more transparent and ensure a more systematic analysis? This book examines the central methodological and theoretical issues involved in using computers in qualitative research. International experts in the field discuss various strategies for computer-assisted qualitative analysis, outlining strategies for building theories by employing networks of categories and means of evaluating hypotheses generated from qualitative data. New ways of integrating qualitative and quantitative analysis techniques are also described.

Introduction to Information Visualization: Transforming Data into Meaningful Information is for anyone interested in the art and science of communicating data to others. It shows readers how to transform data into something meaningful - information. Applying information visualization in research, service, teaching, and professional life requires a solid understanding of graphic design and the aesthetic along with hands-on skills and knowledge of data principles and software. This book is applicable to students in all domains, to researchers who need to understand how to create graphics that explain their data, and to professionals and administrators for professional development training. Website Designers and Human-Computer Interaction researchers will appreciate the backstory of designing interactive visualizations for the web. Drawing on the author's years of practice and teaching, it bridges the two worlds in ways everyone can participate in the future of information and to appreciate the beautiful in information: oStep-by-step directions in the fundamentals of HTML5, CSS, and d3.js oDesign challenges with fully explained answers oWeb-site support for code samples (JavaScript, d3.js, python), live examples, and a place to build a community of other IV pros oUseful for teaching design to scientists; data to the humanities oGuidance for using the text depending on the class makeup oReview of third-party visualization software, big data trends, and script libraries oGuidance on how to continue in the IV world after graduation This full-color book features graphics and a companion Web site. The online companion site hosts living examples, updates, and errata. You're invited to participate on the site, too, sharing your questions, solutions, and ideas. For most readings, there is a partner design lab. At the conclusion of the course, there is a complete interactive information visualization service documentation for libraries.

It is not lost on commercial organisations that where we live colours how we view ourselves and others. That is why so many now place us into social groups on the basis of the type of postcode in which we live. Social scientists call this practice "commercial sociology". Richard Webber originated Acorn and Mosaic, the two most successful geodemographic classifications. Roger Burrows is a critical interdisciplinary social scientist. Together they chart the origins of this practice and explain the challenges it poses to long-established social scientific beliefs such as: the role of the questionnaire in an era of "big data" the primacy of theory the relationship between qualitative and quantitative modes of understanding the relevance of visual clues to lay understanding. To help readers evaluate the validity of this form of classification, the book assesses how well geodemographic categories track the emergence of new types of residential neighbourhood and subject a number of key contemporary issues to geodemographic modes of analysis.

This book provides an up-to-date picture of the main methods for the quantitative analysis of text.

Popping begins by overviewing the background and the conceptual foundations of the field, introducing the latest developments. He then concentrates on a comprehensive coverage of the traditional thematic approaches of text analysis, followed by the newer developments in semantic and network text analysis methodologies. Finally, the author examines the relationship between content analysis and other kinds of text analysis - from qualitative research, linguistic analysis and information retrieval.

Computer-assisted Text Analysis focuses on the methodological and practical issues of coding and handling data, including sampling, reliability and validity issues, and includes a useful appendix of computer programs for text analysis.

The methods described are applicable across a wide range of disciplines in the social sciences and humanities as well as, for example, practitioners from the fields of political science, journalism., communication, marketing and information systems.

SPSS for Windows is the most widely used computer package for analyzing quantitative data. In a clear, readable, non-technical style, this book teaches beginners how to use the program, input and manipulate data, use descriptive analyses and inferential techniques, including: t-tests, analysis of variance, correlation and regression, nonparametric techniques, and reliability analysis and factor analysis.

The author provides an overview of statistical analysis, and then shows in a simple step-by-step method how to set up an SPSS file in order to run an analysis as well as how to graph and display data. He explains how to use SPSS for all the main statistical approaches you would expect to find in an introductory statistics course.

The book is written for users of Versions 6 and 6.1, but will be equally valuable to users of later versions.

Das Buch bietet einen Einstieg in das Controlling und Management moderner Produktionssysteme mit Hilfe des SAP (R)-ERP-Systems. In praxisnahen Fallbeispielen und zahlreichen Screenshots lernt der Anwender Produktion, Materialplanung und Kostenplanung optimal zu steuern und zu uberwachen. Leicht verstandlich erschliesst sich der Zugang zu den SAP (R)-Modulen CO (R), PP (R), MM (R) und PS (R). ERP-Systeme gehoeren zu den Ankeranwendungen in vielen Branchen, aber auch zum Standardkanon einiger Studiengange. Hier dient das Buch als Lehrunterlage. Die funfte Auflage wurde, basierend auf dem neuesten IDES (R)-Release ECC (R)6.0, aktualisiert und erweitert.

Identity Matching ist die Grundlage fur die Suche mit und nach Personendaten. Und die betreibt heutzutage die ganze Welt: Banken suchen Geldwascher in ihren Kundendateien, Polizeibehoerden uberprufen Verdachtige mit ihren Registern und Privatpersonen stoebern alte Bekannte im Web auf. Mittels Identity Matching besorgen sich Studenten Fachartikel, Journalisten Nachrichten, Vermieter Bonitatsauskunfte und Verkaufer ihre nachsten Marketing-Opfer. Das Problem bisher ist: Sobald wir den Namen nicht genau so schreiben, wie er in der Quelle reprasentiert ist, finden wir ihn nicht. Jetzt hebt die Linguistik das Identity Matching auf ein neues Niveau. Mit dem Wissen uber Sprachen, Schriften und globale Namenskonventionen ist eine zugleich prazise und zuverlassige Personensuche moeglich. Dieses Buch beschreibt, was linguistisches Identity Matching ist, und gibt Ihnen praktische Tipps, wie auch Sie davon profitieren koennen.

Partendo dai temi cari e mai completamente risolti della traduttologia, che si potrebbero esemplificare nell'affermazione per cui la pratica traduttiva e da sempre alla ricerca di una teoria che la spieghi, la modelli e le dia un fondamento scientifico, questo lavoro ha l'ambizione di fornire, adottando l'approccio semiotico della scuola di Parigi, una nuova sistematizzazione della traduzione in quanto concetto, pratica e testo. Le relazioni identitarie e veridittive, articolate nel quadrato semiotico, determinano le condizioni ontologiche della traduzione; la schematizzazione narrativa modellizza la pratica traduttiva ed esplicita le competenze del traduttore, gli aspetti manipolativi e le condizioni aletiche ed etiche insiti nella traduzione. L'analisi si sposta poi su terreni piu empirici e la proposta teorica si misura con il testo tradotto; su quest'ultimo si identificano i rapporti identita-alterita, la dimensione assiologica e la prensione timica del traduttore. La prospettiva generativa permette di situarsi in una dimensione epistemica e metodologica piu ampia, che al contempo impone una riflessione sulle condizioni di felicita specifiche della traduttologia.

The aim of query processing is to find information in one or more databases and deliver it to the user quickly and efficiently. Traditional techniques work well for databases with standard, single-site relational structures, but databases containing more complex and diverse types of data demand new query processing and optimization techniques. Most real-world data is not well structured. Today's databases typically contain much non-structured data such as text, images, video, and audio, often distributed across computer networks. In this complex milieu (typified by the world wide Web), efficient and accurate query processing becomes quite challenging. Principles of Database Query Processing for Advanced Applications teaches the basic concepts and techniques of query processing and optimization for a variety of data forms and database systems, whether structured or unstructured.

This book presents the novel approach of analyzing large-sized rectangular-shaped numerical data (so-called big data). The essence of this approach is to grasp the "meaning" of the data instantly, without getting into the details of individual data. Unlike conventional approaches of principal component analysis, randomness tests, and visualization methods, the authors' approach has the benefits of universality and simplicity of data analysis, regardless of data types, structures, or specific field of science. First, mathematical preparation is described. The RMT-PCA and the RMT-test utilize the cross-correlation matrix of time series, C = XXT, where Xrepresents a rectangular matrix of N rows and L columns and XT represents the transverse matrix of X. Because C is symmetric, namely, C = CT, it can be converted to a diagonal matrix of eigenvalues by a similarity transformation-1 = SCST using an orthogonal matrix S. When N is significantly large, the histogram of the eigenvalue distribution can be compared to the theoretical formula derived in the context of the random matrix theory (RMT, in abbreviation). Then the RMT-PCA applied to high-frequency stock prices in Japanese and American markets is dealt with. This approach proves its effectiveness in extracting "trendy" business sectors of the financial market over the prescribed time scale. In this case, X consists of N stock- prices of lengthL, and the correlation matrix C is an N by N square matrix, whose element at the i-th row and j-th column is the inner product of the price time series of the length L of the i-th stock and the j-th stock of the equal length L. Next, the RMT-test is applied to measure randomness of various random number generators, including algorithmically generated random numbers and physically generated random numbers. The book concludes by demonstrating two application of the RMT-test: (1) a comparison of hash functions, and (2) stock prediction by means of randomness.