Data Smart PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data Smart PDF full book. Access full book title Data Smart by John W. Foreman. Download full books in PDF and EPUB format.
Author: John W. Foreman
Publisher: John Wiley & Sons
ISBN: 1118839862
Category : Business & Economics
Languages : en
Pages : 432
Get Book Here
Book Description
Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.
Author: John W. Foreman
Publisher: John Wiley & Sons
ISBN: 1118839862
Category : Business & Economics
Languages : en
Pages : 432
Get Book Here
Book Description
Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.
Author: Kuan-Ching Li
Publisher: CRC Press
ISBN: 0429018029
Category : Business & Economics
Languages : en
Pages : 477
Get Book Here
Book Description
Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories, data mining and machine learning techniques. The book features contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning, Big Data capture and representation, AI for Big Data applications, and more. Features Presents state-of-the-art research in big data and smart computing Provides a broad coverage of topics in data science and machine learning Combines computing methods with domain knowledge and a focus on applications in science, engineering, and business Covers data security and privacy, including AI techniques Includes contributions from leading researchers
Author: Kuan-Ching Li
Publisher: CRC Press
ISBN: 0429018037
Category : Business & Economics
Languages : en
Pages : 429
Get Book Here
Book Description
Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories, data mining and machine learning techniques. The book features contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning, Big Data capture and representation, AI for Big Data applications, and more. Features Presents state-of-the-art research in big data and smart computing Provides a broad coverage of topics in data science and machine learning Combines computing methods with domain knowledge and a focus on applications in science, engineering, and business Covers data security and privacy, including AI techniques Includes contributions from leading researchers
Author: Jathan Sadowski
Publisher: MIT Press
ISBN: 026253858X
Category : Social Science
Languages : en
Pages : 253
Get Book Here
Book Description
Who benefits from smart technology? Whose interests are served when we trade our personal data for convenience and connectivity? Smart technology is everywhere: smart umbrellas that light up when rain is in the forecast; smart cars that relieve drivers of the drudgery of driving; smart toothbrushes that send your dental hygiene details to the cloud. Nothing is safe from smartification. In Too Smart, Jathan Sadowski looks at the proliferation of smart stuff in our lives and asks whether the tradeoff—exchanging our personal data for convenience and connectivity—is worth it. Who benefits from smart technology? Sadowski explains how data, once the purview of researchers and policy wonks, has become a form of capital. Smart technology, he argues, is driven by the dual imperatives of digital capitalism: extracting data from, and expanding control over, everything and everybody. He looks at three domains colonized by smart technologies' collection and control systems: the smart self, the smart home, and the smart city. The smart self involves more than self-tracking of steps walked and calories burned; it raises questions about what others do with our data and how they direct our behavior—whether or not we want them to. The smart home collects data about our habits that offer business a window into our domestic spaces. And the smart city, where these systems have space to grow, offers military-grade surveillance capabilities to local authorities. Technology gets smart from our data. We may enjoy the conveniences we get in return (the refrigerator says we're out of milk!), but, Sadowski argues, smart technology advances the interests of corporate technocratic power—and will continue to do so unless we demand oversight and ownership of our data.
Author: Soumya Sen
Publisher: John Wiley & Sons
ISBN: 1118611667
Category : Technology & Engineering
Languages : en
Pages : 533
Get Book Here
Book Description
A comprehensive text addressing the high demand for network, cloud, and content services through cutting-edge research on data pricing and business strategies Smart Data Pricing tackles the timely issue of surging demand for network, cloud, and content services and corresponding innovations in pricing these services to benefit consumers, operators, and content providers. The pricing of data traffic and other services is central to the core challenges of network monetization, growth sustainability, and bridging the digital divide. In this book, experts from both academia and industry discuss all aspects of smart data pricing research and development, including economic analyses, system development, user behavior evaluation, and business strategies. Smart Data Pricing: • Presents the analysis of leading researchers from industry and academia surrounding the pricing of network services and content. • Discusses current trends in mobile and wired data usage and their economic implications for content providers, network operators, end users, government regulators, and other players in the Internet ecosystem. • Includes new concepts and background technical knowledge that will help researchers and managers effectively monetize their networks and improve user quality-of-experience. • Provides cutting-edge research on business strategies and initiatives through a diverse collection of perspectives. • Combines academic and industry expertise from multiple disciplines and business organizations. The ideas and background of the technologies and economic principles discussed within these chapters are of real value to practitioners, researchers, and managers in identifying trends and deploying new pricing and network management technologies, and will help support managers in identifying new business directions and innovating solutions to challenging business problems.
Author: Fernando Iafrate
Publisher: John Wiley & Sons
ISBN: 1848217552
Category : Computers
Languages : en
Pages : 88
Get Book Here
Book Description
A pragmatic approach to Big Data by taking the reader on a journey between Big Data (what it is) and the Smart Data (what it is for). Today’s decision making can be reached via information (related to the data), knowledge (related to people and processes), and timing (the capacity to decide, act and react at the right time). The huge increase in volume of data traffic, and its format (unstructured data such as blogs, logs, and video) generated by the “digitalization” of our world modifies radically our relationship to the space (in motion) and time, dimension and by capillarity, the enterprise vision of performance monitoring and optimization.
Author: Wookey Lee
Publisher: Springer Nature
ISBN: 9811587310
Category : Technology & Engineering
Languages : en
Pages : 127
Get Book Here
Book Description
This book covers topics like big data analyses, services, and smart data. It contains (i) invited papers, (ii) selected papers from the Sixth International Conference on Big Data Applications and Services (BigDAS 2018), as well as (iii) extended papers from the Sixth IEEE International Conference on Big Data and Smart Computing (IEEE BigComp 2019). The aim of BigDAS is to present innovative results, encourage academic and industrial interaction, and promote collaborative research in the field of big data worldwide. BigDAS 2018 was held in Zhengzhou, China, on August 19–22, 2018, and organized by the Korea Big Data Service Society and TusStar. The goal of IEEE BigComp, initiated by Korean Institute of Information Scientists and Engineers (KIISE), is to provide an international forum for exchanging ideas and information on current studies, challenges, research results, system developments, and practical experiences in the emerging fields of big data and smart computing. IEEE BigComp 2019 was held in Kyoto, Japan, on February 27–March 02, 2019, and co-sponsored by IEEE and KIISE.
Author: James A. George
Publisher: John Wiley & Sons
ISBN: 9780470583043
Category : Technology & Engineering
Languages : en
Pages : 400
Get Book Here
Book Description
The authors advocate attention to smart data strategy as an organizing element of enterprise performance optimization. They believe that “smart data” as a corporate priority could revolutionize government or commercial enterprise performance much like “six sigma” or “total quality” as organizing paradigms have done in the past. This revolution has not yet taken place because data historically resides in the province of the information resources organization. Solutions that render data smart are articulated in “technoid” terms versus the language of the board room. While books such as Adaptive Information by Pollock and Hodgson ably describe the current state of the art, their necessarily technical tone is not conducive to corporate or agency wide qualitative change.
Author: Nilanjan Dey
Publisher: CRC Press
ISBN: 0429804571
Category : Computers
Languages : en
Pages : 225
Get Book Here
Book Description
The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Ontologies that are used in heterogeneous IoT environments have been discussed including interpretation, context awareness, analyzing various data sources, machine learning algorithms and intelligent services and applications. Further, it includes unsupervised and semi-supervised machine learning techniques with study of semantic analysis and thorough analysis of reviews. Divided into sections such as machine learning, security, IoT and data mining, the concepts are explained with practical implementation including results. Key Features Follows an algorithmic approach for data analysis in machine learning Introduces machine learning methods in applications Address the emerging issues in computing such as deep learning, machine learning, Internet of Things and data analytics Focuses on machine learning techniques namely unsupervised and semi-supervised for unseen and seen data sets Case studies are covered relating to human health, transportation and Internet applications
Author: R. Asokan
Publisher: Springer Nature
ISBN: 9819731917
Category :
Languages : en
Pages : 668
Get Book Here
Book Description
