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Starting an Etsy Business For Dummies (Third Edition)
by Allison Strine Kate Gatski Kate Shoup<p>Turn your hobby into revenue with an expertly-run Etsy shop <p><i>Starting an Etsy Business For Dummies</i> is the all-in-one resource for building your own successful business. Arts and crafts are currently a $32 billion market in the U.S., and Etsy is the number-one way to grab a piece of it for yourself. Sales through the site are rising, fueled by Pinterest, Instagram, and other social media—so there's never been a better time to jump into the fray. This book shows you everything you need to know to get set up, get things running, and build your business as you see fit. From photography and sales writing, through SEO, homepage navigation, and more, you'll find it all here. <p>This new third edition has been updated to cover Etsy's newest seller tools, including Pattern, Etsy Manufacturing, Etsy Shop Updates, and the Dashboard, with expert guidance on QuickBooks Self-Employed to help you keep your business's finances under control. With helpful information, tips, tools, and tricks, this book is your ultimate guide to building your own Etsy shop. <p> <li>Showcase your products to their best advantage with great photographs and compelling listings <li>Learn the technical side of setting up shop and processing orders <li>Manage your storefront efficiently using the latest Etsy tools and features <li>Increase sales by connecting with other vendors and promoting on Pinterest</li> <p> <p>Are you an artist, crafter, artisan, or craftsman? Etsy can be another great revenue stream. Are you just curious about whether your projects would sell? Wade in gradually to test the waters. Etsy is home to businesses of many sizes and types, and <i>Starting an Etsy Business For Dummies</i> shows you how to stake your claim.</p>
Starting Out With C++: Early Objects
by Tony Gaddis Judy Walters Godfrey MugandaFor courses in C++ Programming. Fundamentals of C++ for Novices and Experienced Programmers Alike Intended for use in a two-term, three-term, or accelerated one-term C++ programming sequence, this Ninth Edition of Starting Out with C++: Early Objects introduces the fundamentals of C++ to novices and experienced programmers alike. In clear, easy-to-understand terms, the text introduces all of the necessary topics for beginning C++ programmers. Real-world examples allow readers to apply their knowledge in understanding how, why, and when to implement the features of C++. The text is organized in a progressive, step-by-step fashion that allows for flexibility. Building on the popularity of previous editions, the Ninth Edition has been updated and enhanced with new material, including C++11 topics and recent changes in technology.
Starting out with Visual Basic (3rd Custom LACC Edition)
by Tony Gaddis Kip IrvibeStarting out with Visual Basic. Third Custom Edition for Los Angeles City College.
Startups revolucionárias: Elimine a Concorrência Com Sua Startup Inovadora
by Jonathan S. WalkerComece o seu negócio como nunca antes possível com essas estratégias vitais Deseja que sua startup comece da melhor maneira sem muito esforço? Você precisa atrair possíveis investidores para obter uma vantagem sobre a concorrência? Você quer ganhar impulso rápido para que sua startup cresça exponencialmente nos próximos meses? Apresentando Startups Revolucionárias: Esmague a Concorrência Com Sua Startup Inovadora! As estratégias comprovadas para levar sua empresa aonde ela precisa ir. Aqui estão algumas das coisas que você aprenderá neste livro para começar bem o seu negócio: Ganhando tração para sua startup Usando e-mails para sua vantagem Capitalizando no Marketing por Email (principais estratégias para campanhas) Estratégias de Marketing Viral Dimensionamento de Pequena para Larga Escala Como se Alavancar no Marketing de Afiliados Aproveitando o Poder do Marketing de Rede para sua Startup E muito, muito mais! Pegue sua cópia deste livro hoje! Não perca todas as coisas incríveis reunidas neste poderoso livro de estratégia de negócios. O preço pode subir logo, então se apresse! Vá até o topo e pressione o botão "Comprar agora" hoje!
Statistical Analysis with R For Dummies
by Joseph SchmullerUnderstanding the world of R programming and analysis has never been easier Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming. People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results. Gets you up to speed on the #1 analytics/data science software tool Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling Shows you how R offers intel from leading researchers in data science, free of charge Provides information on using R Studio to work with R Get ready to use R to crunch and analyze your data—the fast and easy way!
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Third Edition
by Bruce RatnerInterest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third edition of this bestseller, the author has completely revised, reorganized, and repositioned the original chapters and produced 13 new chapters of creative and useful machine-learning data mining techniques. In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. What is new in the Third Edition: The current chapters have been completely rewritten. The core content has been extended with strategies and methods for problems drawn from the top predictive analytics conference and statistical modeling workshops. Adds thirteen new chapters including coverage of data science and its rise, market share estimation, share of wallet modeling without survey data, latent market segmentation, statistical regression modeling that deals with incomplete data, decile analysis assessment in terms of the predictive power of the data, and a user-friendly version of text mining, not requiring an advanced background in natural language processing (NLP). Includes SAS subroutines which can be easily converted to other languages. As in the previous edition, this book offers detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. The author addresses each methodology and assigns its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.
Statistical Language and Speech Processing: 5th International Conference, SLSP 2017, Le Mans, France, October 23–25, 2017, Proceedings (Lecture Notes in Computer Science #10583)
by Nathalie Camelin, Yannick Estève and Carlos Martín-VideThis book constitutes the refereed proceedings of the 5th International Conference on Statistical Language and Speech Processing, SLSP 2017, held in Le Mans, France, in October 2017. The 21 full papers presented were carefully reviewed and selected from 39 submissions. The papers cover topics such as anaphora and conference resolution; authorship identification, plagiarism and spam filtering; computer-aided translation; corpora and language resources; data mining and semanticweb; information extraction; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural language understanding; neural representation of speech and language; opinion mining and sentiment analysis; parsing; part-of-speech tagging; question and answering systems; semantic role labeling; speaker identification and verification; speech and language generation; speech recognition; speech synthesis; speech transcription; speech correction; spoken dialogue systems; term extraction; text categorization; test summarization; user modeling. They are organized in the following sections: language and information extraction; post-processing and applications of automatic transcriptions; speech paralinguistics and synthesis; speech recognition: modeling and resources.
Statistical Regression and Classification: From Linear Models to Machine Learning (Chapman & Hall/CRC Texts in Statistical Science)
by Norman Matloff<p>Statistical Regression and Classification: From Linear Models to Machine Learning takes an innovative look at the traditional statistical regression course, presenting a contemporary treatment in line with today's applications and users. <p>The book treats classical regression methods in an innovative, contemporary manner. Though some statistical learning methods are introduced, the primary methodology used is linear and generalized linear parametric models, covering both the Description and Prediction goals of regression methods. The author is just as interested in Description applications of regression, such as measuring the gender wage gap in Silicon Valley, as in forecasting tomorrow's demand for bike rentals. An entire chapter is devoted to measuring such effects, including discussion of Simpson's Paradox, multiple inference, and causation issues. Similarly, there is an entire chapter of parametric model fit, making use of both residual analysis and assessment via nonparametric analysis.</p>
Statistics for Data Science
by James D. MillerGet your statistics basics right before diving into the world of data science About This Book • No need to take a degree in statistics, read this book and get a strong statistics base for data science and real-world programs; • Implement statistics in data science tasks such as data cleaning, mining, and analysis • Learn all about probability, statistics, numerical computations, and more with the help of R programs Who This Book Is For This book is intended for those developers who are willing to enter the field of data science and are looking for concise information of statistics with the help of insightful programs and simple explanation. Some basic hands on R will be useful. What You Will Learn • Analyze the transition from a data developer to a data scientist mindset • Get acquainted with the R programs and the logic used for statistical computations • Understand mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more • Learn to implement statistics in data science tasks such as data cleaning, mining, and analysis • Learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks • Get comfortable with performing various statistical computations for data science programmatically In Detail Data science is an ever-evolving field, which is growing in popularity at an exponential rate. Data science includes techniques and theories extracted from the fields of statistics; computer science, and, most importantly, machine learning, databases, data visualization, and so on. This book takes you through an entire journey of statistics, from knowing very little to becoming comfortable in using various statistical methods for data science tasks. It starts off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for statistical computation are clearly explained along with logic. You will come across various mathematical concepts, such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis. You will learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks. By the end of the book, you will be comfortable with performing various statistical computations for data science programmatically. Style and approach Step by step comprehensive guide with real world examples
Statistics for Machine Learning
by Pratap DangetiBuild Machine Learning models with a sound statistical understanding. About This Book • Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics. • Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering. • Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python. Who This Book Is For This book is intended for developers with little to no background in statistics, who want to implement Machine Learning in their systems. Some programming knowledge in R or Python will be useful. What You Will Learn • Understand the Statistical and Machine Learning fundamentals necessary to build models • Understand the major differences and parallels between the statistical way and the Machine Learning way to solve problems • Learn how to prepare data and feed models by using the appropriate Machine Learning algorithms from the more-than-adequate R and Python packages • Analyze the results and tune the model appropriately to your own predictive goals • Understand the concepts of required statistics for Machine Learning • Introduce yourself to necessary fundamentals required for building supervised & unsupervised deep learning models • Learn reinforcement learning and its application in the field of artificial intelligence domain In Detail Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. You will also design programs for performing tasks such as model, parameter fitting, regression, classification, density collection, and more. By the end of the book, you will have mastered the required statistics for Machine Learning and will be able to apply your new skills to any sort of industry problem. Style and approach This practical, step-by-step guide will give you an understanding of the Statistical and Machine Learning fundamentals you'll need to build models.
Statistics for Managers Using Microsoft Excel
by David Levine David Stephan Kathryn Szabat<p>For undergraduate business statistics courses. Analyzing the Data Applicable to Business. This text is the gold standard for learning how to use Microsoft Excel® in business statistics, helping students gain the understanding they need to be successful in their careers. The authors present statistics in the context of specific business fields; full chapters on business analytics further prepare students for success in their professions. Current data throughout the text lets students practice analyzing the types of data they will see in their professions. The friendly writing style include tips throughout to encourage learning. <p>The book also integrates PHStat, an add-in that bolsters the statistical functions of Excel.</p>
Statistik mit Excel für Dummies (Für Dummies)
by Joseph SchmullerStatistiken und Aussagen zu Wahrscheinlichkeiten begegnen uns heute überall: Die Umsatzentwicklung in Unternehmen, Hochrechnungen für Wahlergebnisse, PISA-Ergebnisse fünfzehnjähriger Schüler sind nur drei von zahlreichen Beispielen. Joseph Schmuller zeigt Ihnen in diesem Buch, wie Sie die Zahlen in den Griff bekommen und Daten, Statistiken und Wahrscheinlichkeiten richtig lesen und interpretieren. Dafür brauchen Sie keinen Statistikkurs zu belegen und kein Mathegenie zu sein. Für alles gibt es in Excel die passende Funktion und das passende Werkzeug. So können Sie Theorie und Praxis sofort miteinander verbinden.
Statistik mit R für Dummies (Für Dummies)
by Joseph SchmullerAls angehender Wissenschaftler, Manager oder Unternehmensberater sind Sie darauf angewiesen, Daten mit statistischen Methoden fehlerfrei auszuwerten und die Ergebnisse überzeugend darzustellen? Statistik ist allerdings nicht gerade Ihr Fachgebiet? Dann ist dieses Buch genau richtig für Sie. In jedem Kapitel führt der Autor eine statistische Methode vor und erklärt, was man an den Ergebnissen ablesen kann und was nicht. Unmittelbar im Anschluss beschreibt er, wie man die Methode in R implementiert. Denn R lässt mit den dazugehörigen Paketen keine Wünsche in der Statistik offen. In der Regel genügen wenige Zeilen Programmcode. Und das Beste ist: Die statistischen Pakete von R sind kostenlos. Dieses Buch hilft, bessere Entscheidungen zu treffen und Datenmüll zu vermeiden.
Stop Motion: Craft Skills For Model Animation
by Susannah ShawStop motion animation is a challenging and time-consuming skill that requires patience, adaptability, and a close eye to detail. Stop Motion: Craft Skills for Model Animation, 3rd Edition is the essential guide to help stop motion animators overcome these challenges of this highly-skilled craft. Author Susannah Shaw provides a step-by-step guide to creating successful stop motioin films. Starting with some basic exercises, the reader will learn about developing a story, making models, creating sets and props, the mechanics of movements, filming postproduction, and how to set about finding that first elusive job in a modern studio. Key Features Interviews with current stars, step-by-step examples, coverage of Rapid Prototyping and Dragonframe Software
Story Structure and Development: A Guide for Animators, VFX Artists, Game Designers, and Virtual Reality
by Craig CaldwellProfessor Craig Caldwell’s Story Structure and Development offers a clear approach to the essentials of story. It lays out the fundamental elements, principles, and structure for animators, designers, and artists so they can incorporate these concepts in their work. As a practical guide it includes extensive insights and advice from industry professionals. Readers will learn the universal patterns of story and narrative used in today’s movies, animation, games, and VR. With over 200 colorful images, this book has been designed for visual learners, and is organized to provide access to story concepts for the screen media professional and student. Readers will discover the story fundamentals referred to by every director and producer when they say "It’s all about story".
Storytelling for Interactive Digital Media and Video Games
by Nicholas ZemanThe evolution of story-telling is as old as the human race; from the beginning, when our ancestors first gathered around a campfire to share wondrous tales through oral traditions, to today, with information and stories being shared through waves and filling screens with words and images. Stories have always surrounded us, and united us in ways other disciplines can't. Storytelling for Interactive Digital Media and Video Games lays out the construct of the story, and how it can be manipulated by the storyteller through sound, video, lighting, graphics, and color. This book is the perfect guide to aspiring storytellers as it illustrates the different manner of how and why stories are told, and how to make them "interactive." Storytelling features heavy game development as a method of storytelling and delivery, and how to develop compelling plots, characters, settings, and actions inside a game. The concept of digital storytelling will be explored, and how this differs from previous incarnations of mediums for stories Key Features: Explores the necessary elements of a story (setting, character, events, sequence, and perspective) and how they affect the viewer of the story Discusses media and its role in storytelling, including images, art, sound, video, and animation Explores the effect of interactivity on the story, such as contest TV, web-based storytelling, kiosks, and games Shows the different types of story themes in gaming and how they are interwoven Describes how to make games engaging and rewarding intrinsically and extrinsically
Strategic A2/AD in Cyberspace
by Russell Alison LawlorStrategic A2/AD in Cyberspace focuses on exclusion from cyberspace, or the ability of a state to be cut off entirely from cyberspace. Strategic anti-access and area denial (A2/AD) operations are common in other domains, but, before now, they have not been examined for their relevance to cyberspace. This book examines how strategic A2/AD operations can cut off states from cyberspace through attacks at either the physical or logic layers of cyberspace. The result of strategic cyber A2/AD operations could be catastrophic for modern economies, governments, military forces, and societies, yet there has been surprisingly little study of these threats to states' access to cyberspace. This book examines the implications of strategic cyber A2/AD operations for deterrence strategy and proposes a new view of how exclusion from cyberspace can be used as a coercive tool in diplomacy.
Strategic Engineering for Cloud Computing and Big Data Analytics
by Amin Hosseinian-Far Muthu Ramachandran Dilshad SarwarThis book demonstrates the use of a wide range of strategic engineering concepts, theories and applied case studies to improve the safety, security and sustainability of complex and large-scale engineering and computer systems. It first details the concepts of system design, life cycle, impact assessment and security to show how these ideas can be brought to bear on the modeling, analysis and design of information systems with a focused view on cloud-computing systems and big data analytics. This informative book is a valuable resource for graduate students, researchers and industry-based practitioners working in engineering, information and business systems as well as strategy.
The Strategic Storyteller: Content Marketing in the Age of the Educated Consumer
by Alexander JutkowitzThe world needs more storytellers. Storytelling is an inherently innovative activity. When organizations find their best stories and tell them to the world, they’re not only building a reputation, they're flexing the same muscles that allow them to pivot quickly around crisis or opportunity, and solve problems more creatively. For individuals, crafting stories is the primary way we can make sense of the world and our place in it. The Strategic Storyteller is a comprehensive, practical guide to transformative storytelling. In its pages you will learn how to: Tap into your and your organization's unique sources of wonder, wisdom, and delight Boost individual and collective creativity Understand the storytelling strategies behind some of the world’s most powerful brands Unlock the secrets of the great strategic storytellers of the past Build a place where your stories can live online Distribute stories so they have staying power and reach in the digital age Convene audiences by going beyond demographic stereotypes and tapping into enduring human needs Understand how unshakable reputations are built out of stories that accumulate over time Sooner or later all of us will be asked to tell stories in the course of our professional lives. We will be asked to make a case for ourselves, our work, our companies, and our future. The Strategic Storyteller tells you how.
Stream Analytics with Microsoft Azure
by Anindita Basak Krishna Venkataraman Ryan Murphy Manpreet SinghDevelop and manage effective real-time streaming solutions by leveraging the power of Microsoft Azure About This Book • Analyze your data from various sources using Microsoft Azure Stream Analytics • Develop, manage and automate your stream analytics solution with Microsoft Azure • A practical guide to real-time event processing and performing analytics on the cloud Who This Book Is For If you are looking for a resource that teaches you how to process continuous streams of data in real-time, this book is what you need. A basic understanding of the concepts in analytics is all you need to get started with this book What You Will Learn • Perform real-time event processing with Azure Stream Analysis • Incorporate the features of Big Data Lambda architecture pattern in real-time data processing • Design a streaming pipeline for storage and batch analysis • Implement data transformation and computation activities over stream of events • Automate your streaming pipeline using Powershell and the .NET SDK • Integrate your streaming pipeline with popular Machine Learning and Predictive Analytics modelling algorithms • Monitor and troubleshoot your Azure Streaming jobs effectively In Detail Microsoft Azure is a very popular cloud computing service used by many organizations around the world. Its latest analytics offering, Stream Analytics, allows you to process and get actionable insights from different kinds of data in real-time. This book is your guide to understanding the basics of how Azure Stream Analytics works, and building your own analytics solution using its capabilities. You will start with understanding what Stream Analytics is, and why it is a popular choice for getting real-time insights from data. Then, you will be introduced to Azure Stream Analytics, and see how you can use the tools and functions in Azure to develop your own Streaming Analytics. Over the course of the book, you will be given comparative analytic guidance on using Azure Streaming with other Microsoft Data Platform resources such as Big Data Lambda Architecture integration for real time data analysis and differences of scenarios for architecture designing with Azure HDInsight Hadoop clusters with Storm or Stream Analytics. The book also shows you how you can manage, monitor, and scale your solution for optimal performance. By the end of this book, you will be well-versed in using Azure Stream Analytics to develop an efficient analytics solution that can work with any type of data. Style and approach A comprehensive guidance on developing real-time event processing with Azure Stream Analysis
Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications
by Vasiliki Kalavri Fabian HueskeGet started with Apache Flink, the open source framework that powers some of the world’s largest stream processing applications. With this practical book, you’ll explore the fundamental concepts of parallel stream processing and discover how this technology differs from traditional batch data processing.Longtime Apache Flink committers Fabian Hueske and Vasia Kalavri show you how to implement scalable streaming applications with Flink’s DataStream API and continuously run and maintain these applications in operational environments. Stream processing is ideal for many use cases, including low-latency ETL, streaming analytics, and real-time dashboards as well as fraud detection, anomaly detection, and alerting. You can process continuous data of any kind, including user interactions, financial transactions, and IoT data, as soon as you generate them.Learn concepts and challenges of distributed stateful stream processingExplore Flink’s system architecture, including its event-time processing mode and fault-tolerance modelUnderstand the fundamentals and building blocks of the DataStream API, including its time-based and statefuloperatorsRead data from and write data to external systems with exactly-once consistencyDeploy and configure Flink clustersOperate continuously running streaming applications
Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming
by Gerard Maas Francois GarillotBefore you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. You’ll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs.Authors Gerard Maas and François Garillot help you explore the theoretical underpinnings of Apache Spark. This comprehensive guide features two sections that compare and contrast the streaming APIs Spark now supports: the original Spark Streaming library and the newer Structured Streaming API.Learn fundamental stream processing concepts and examine different streaming architecturesExplore Structured Streaming through practical examples; learn different aspects of stream processing in detailCreate and operate streaming jobs and applications with Spark Streaming; integrate Spark Streaming with other Spark APIsLearn advanced Spark Streaming techniques, including approximation algorithms and machine learning algorithmsCompare Apache Spark to other stream processing projects, including Apache Storm, Apache Flink, and Apache Kafka Streams
Streaming Data: Understanding the real-time pipeline
by Andrew PsaltisSummaryStreaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyAs humans, we're constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them.About the BookStreaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you'll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you'll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details.What's InsideThe right way to collect real-time dataArchitecting a streaming pipelineAnalyzing the dataWhich technologies to use and whenAbout the ReaderWritten for developers familiar with relational database concepts. No experience with streaming or real-time applications required.About the AuthorAndrew Psaltis is a software engineer focused on massively scalable real-time analytics.Table of ContentsPART 1 - A NEW HOLISTIC APPROACHIntroducing streaming dataGetting data from clients: data ingestionTransporting the data from collection tier: decoupling the data pipelineAnalyzing streaming dataAlgorithms for data analysisStoring the analyzed or collected dataMaking the data availableConsumer device capabilities and limitations accessing the dataPART 2 - TAKING IT REAL WORLDAnalyzing Meetup RSVPs in real time
Streampunks: Youtube y los rebeldes que estan transformando los medios
by Robert Kyncl<P>En los últimos diez años, la plataforma de videos por internet YouTube ha cambiado los medios y el entretenimiento tan profundamente como lo hicieron la invención del cine, la radio y la televisión. <P>Streampunks es una mirada a esta empresa advenediza que examina cómo ha evolucionado YouTube y hacia dónde va. <P>Basándose en relatos de las estrellas más influyentes de YouTube (Streampunks como Tyler Oakley, Lilly Singh y Casey Neistat) y los negociadores que promueven el futuro del entretenimiento (como Scooter Braun y Shane Smith), Robert Kyncl utiliza sus experiencias en tres de las compañías de medios más innovadoras, HBO, Netflix y Youtube, para contar la historia del streaming y de este monstruo moderno de la cultura pop. <P>En colaboración con Maany Peyvan (escritor de contenido de Google), Kyncl explica cómo se dictan las nuevas reglas del entretenimiento y cómo y por qué el panorama de los medios está cambiando radicalmente.
A Study into the Design of Steerable Microphone Arrays (SpringerBriefs in Electrical and Computer Engineering)
by Chiong Ching Lai Sven Erik Nordholm Yee Hong LeungThe book covers the design formulations for broadband beamformer targeting nearfield and farfield sources. The book content includes background information on the acoustic environment, including propagation medium, the array geometries, signal models and basic beamformer designs. Subsequently it introduces design formulation for nearfield, farfield and mixed nearfield-farfield beamformers and extends the design formulation into electronically steerable beamformers. In addition, a robust formulation is introduced for all the designs mentioned.