Deep Learning in Data Analytics: Recent Techniques, Practices and Applications, Acharjya Debi Prasanna, Mitra Anirban, Zaman Noor
Автор: Martin Kleppmann Название: Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems ISBN: 1449373321 ISBN-13(EAN): 9781449373320 Издательство: Wiley Рейтинг: Цена: 50680.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data.
Автор: Solomon Michael G. Название: Blockchain Data Analytics for Dummies ISBN: 1119651778 ISBN-13(EAN): 9781119651772 Издательство: Wiley Рейтинг: Цена: 27450.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 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 dataDiscover the power and potential of blockchain analyticsEstablish data models and quickly mine for insights and resultsCreate data visualizations from blockchain analysis Discover how blockchains are disrupting the data world with this exciting title in the trusted For Dummies line!
Автор: Witten, Ian H. Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed. ISBN: 0128042915 ISBN-13(EAN): 9780128042915 Издательство: Elsevier Science Рейтинг: Цена: 61750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Abu-Salih Bilal, Wongthongtham Pornpit, Zhu Dengya Название: Social Big Data Analytics: Practices, Techniques, and Applications ISBN: 9813366516 ISBN-13(EAN): 9789813366510 Издательство: Springer Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Chapter 1: Big data technologies
Big data is no more "all just hype" but widely applied in nearly all aspects of our business, governments, and organizations with the technology stack of AI. Its influences are far beyond a simple technique innovation but involves all rears in the world. This chapter will first have historical review of big data; followed by discussion of characteristics of big data, i.e. the 3V's to up 10V's of big data. The chapter then introduces technology stacks for an organization to build a big data application, from infrastructure/platform/ecosystem to constructional units/components; following by several successful examples. Finally, we provide some big data online resources for reference.
Chapter 2: Credibility and influence in social big data
Online Social Networks (OSNs) are a fertile medium through which users can express their sentiments and share their opinions, experiences and knowledge of several topics. There is a deficiency of assessment mechanisms that incorporate domain-based trustworthiness. In OSNs, determining users' influence in a particular domain has been driven by its significance in a broad range of applications such as personalized recommendation systems, opinion analysis, expertise retrieval, to name a few. This chapter presents a comprehensive framework that aims to infer value from BSD by measuring the domain-based trustworthiness of OSN users, addressing the main features of big data, and incorporating semantic analysis and the temporal factor.
Chapter 3: Semantic data discovery from social big data
The challenge of managing and extracting useful knowledge from social media data sources has attracted much attention from academia and industry. Social big data is an important big data island; thus, social data analytics are intended to make sense of data and to obtain value from data. Social big data provides a wealth of information that businesses, political governments, organisations, etc. can mine and analyse to exploit value in a variety of areas. This chapter discusses the development of an approach that aims to semantically analyse social content, thus enriching social data with semantic conceptual representation for domain-based discovery.
Chapter 4: Predictive analytics using social big data and machine learning
Previous works in the area of topic distillation and discovery lack an appropriate and applicable technical solution that can handle the complex task of obtaining an accurate interpretation of the contextual social content. This is evident through the inadequacy of these endeavours in addressing the topics of microblogging short messages like tweets, and their inability to classify and predict the messages' actual and precise domains of interest at the user level. Hence, this chapter intends to address this problem by presenting solutions to domain-based classification and prediction of social big data at the user and tweet levels incorporating comprehensive knowledge discovery tools and well-known machine learning algorithms.
Chapter 5: Affective design in the era of big social data
In today's competitive market, product designers not only need to optimize functional qualities when developing a new product, but also they need to optimize the affective qualities of the product. The reason is that products with high affective qualities is more likely to attract more potential consumers to buy. In the past, affective design is generally conducted based on the limited amount of customer survey data which is collected from marketing questionnaires and consumer interviews. Since the data amount is limited, the affective design cannot fully reflect the current or even the recent situation of the marketplaces. Thanks to the advanced computing and web technologies, big data from social media or product reviews in w
Автор: Galit Shmueli, Peter C. Bruce, Nitin R. Patel Название: Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner ISBN: 1118729277 ISBN-13(EAN): 9781118729274 Издательство: Wiley Рейтинг: Цена: 118270.00 T Наличие на складе: Поставка под заказ. Описание: Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.
Автор: Pani Subhendu Kumar, Singh Sanjay Kumar, Garg Lalit Название: Intelligent Data Analytics for Terror Threat Prediction: Architectures, Methodologies, Techniques, and Applications ISBN: 1119711096 ISBN-13(EAN): 9781119711094 Издательство: Wiley Рейтинг: Цена: 193190.00 T Наличие на складе: Поставка под заказ. Описание: For centuries people have recognised the importance of language in creating and applying law. This edited volume shows scholars and students how modern linguistics and related fields contribute to understanding the role language plays, and what follows from viewing law`s power as a matter of situated communication in specific social relations rather than an abstract system of rules.
Автор: Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel Название: Data Mining for Business Analytics: Concepts, Techniques and Applications in Python ISBN: 1119549841 ISBN-13(EAN): 9781119549840 Издательство: Wiley Рейтинг: Цена: 116110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Sometimes you get tired, doing this thing we call justice. You feel burned out or disillusioned. Sometimes you just need a word from the Lord. In these daily devotions, Donna Barber offers life-giving words of renewal and hope for those engaged in the resistance to injustice. When your legs are tired from marching and your knees are bruised from kneeling, you can experience rest and healing.
As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.
Here are just a dozen of the many questions answered within these pages:
What does quantitative analysis of a system really mean?
What is a system?
What are big data and analystics?
How do you know your numbers are good?
What will the future data science environment look like?
How do you determine data provenance?
How do you gather and process information, and then organize, store, and synthesize it?
How does an organization implement data analytics?
Do you really need to think like a Chief Information Officer?
What is the best way to protect data?
What makes a good dashboard?
What is the relationship between eating ice cream and getting attacked by a shark?
The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).
Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.
Автор: Grigsby Mike Название: Marketing Analytics: A Practical Guide to Improving Consumer Insights Using Data Techniques ISBN: 0749482168 ISBN-13(EAN): 9780749482169 Издательство: Неизвестно Рейтинг: Цена: 42230.00 T Наличие на складе: Невозможна поставка. Описание: Understand how to apply marketing science techniques fearlessly, to improve consumer insights and compete more effectively in the marketplace.
Transform your app ideas into fully functional prototypes with the help of expert tips and best practices from Mendix partners
Key Features
Meet the ever-increasing demand for software solution delivery without having to write any code
Build high-availability, low-cost applications unlike those developed via a traditional software engineering approach
Explore Mendix from product design through to delivery using real-world scenarios
Book Description
Low-code is a visual approach to application development. It enables developers of varying experience levels to create web and mobile apps using drag-and-drop components and model-driven logic through a graphic user interface. Mendix is among the fastest-growing platforms that enable low-code enthusiasts to put their software ideas into practice without having to write much code, and Building Low-Code Applications with Mendix will help you get up and running with the process using examples and practice projects.
The book starts with an introduction to Mendix, along with the reasons for using this platform and its tools for creating your first app. As you progress, you'll explore Mendix Studio Pro, the visual environment that will help you learn Mendix app creation. Once you have your working app ready, you'll understand how to enhance it with custom business logic and rules. Next, you'll find out how to defend your app against bad data, troubleshoot and debug it, and finally, connect it with real-world business platforms. You'll build practical skills as the book is filled with examples, real-world scenarios, and explanations of the tools needed to help you build low-code apps successfully.
By the end of this book, you'll have understood the concept of low-code development, learned how to use Mendix effectively, and developed a working app.
What You Will Learn
Gain a clear understanding of what low-code development is and the factors driving its adoption
Become familiar with the various features of Mendix for rapid application development
Discover concrete use cases of Studio Pro
Build a fully functioning web application that meets your business requirements
Get to grips with Mendix fundamentals to prepare for the Mendix certification exam
Understand the key concepts of app development such as data management, APIs, troubleshooting, and debugging
Who this book is for
This book is for tech-savvy business analysts and citizen developers who want to get started with Mendix for rapid mobile and web application development. The book is also helpful for seasoned developers looking to learn a new tool/platform and for anyone passionate about designing technical solutions without wanting to indulge in the complexities of writing code. The book assumes beginner-level knowledge of object-oriented programming and the ability to translate technical solutions from business requirements.
Автор: B. Baesens, D. Roesch, H. Scheule Название: Credit Risk Analytics - Measurement Techniques, Applications, and Examples in SAS ISBN: 1119143985 ISBN-13(EAN): 9781119143987 Издательство: Wiley Рейтинг: Цена: 71810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management.
Автор: Anil Kumar, Manoj Kumar Dash, Shrawan Kumar Trivedi, Tapan Kumar Panda Название: Handbook of Research on Intelligent Techniques and Modeling Applications in Marketing Analytics ISBN: 1522509976 ISBN-13(EAN): 9781522509974 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 267030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Features innovative research and implementation practices of analytics in marketing research. Highlighting various techniques in acquiring and deciphering marketing data, this publication is a pivotal reference for professionals, managers, market researchers, and practitioners interested in the observation and utilization of data on marketing trends to promote positive business practices.
Казахстан, 010000 г. Астана, проспект Туран 43/5, НП2 (офис 2) ТОО "Логобук" Тел:+7 707 857-29-98 ,+7(7172) 65-23-70 www.logobook.kz
