Database design and theory Books
O'Reilly Media Machine Learning and Data Science Blueprints for
Book SynopsisOver the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry.
£47.99
O'Reilly Media Tableau Desktop Pocket Reference
Book SynopsisIn a crowded field of data visualization and analytics tools, Tableau Desktop has emerged as the clear leader. With this handy pocket reference, author Ryan Sleeper (Innovative Tableau) shows you how to translate the vast amounts of data into useful information.
£27.82
University of Nebraska Press The Nature of Data
Book SynopsisBy synthesizing scholarly work at the intersection of political ecology, digital geography, and science and technology studies, The Nature of Data analyzes how new digital technologies affect environments and their control.Trade Review"This book is a necessary piece to lay the groundwork for a political ecology of data and urge more research in this direction. . . . A welcome integration of digital social sciences, political ecology, critical GIS, and science and technology studies, and as such which will be of interest to scholars across these fields, but also to conservation practitioners. This collection of essays might also be useful as a methodological text for advanced graduate students."—Anne-Lise Boyer, H-Environment"Thanks to insights from ecomedia studies, environmental humanists are increasingly studying how the environment becomes digital and the digital becomes environmental. The Nature of Data ably contributes to this research."—Heather Houser, ISLE“Data may not grow on trees, but it increasingly shapes how humans know, govern, and struggle over forests—and indeed, much of the nonhuman world. The Nature of Data captures this moment empirically while advancing political ecology conceptually. An altogether stellar volume.”—Susanne Freidberg, author of Fresh: A Perishable History“In accelerating ways, environmental politics are data politics. This powerful book shows what this looks like in different settings and at different scales, persuasively calling for a new subfield focused on the political ecology of data. Extending from prior work on the delimitations and politics of environmental science, the collection draws out what environmental data can help us see, what it cuts out, and how environmental data production itself is both polluting and weighted by commercial interests.”—Kim Fortun, author of Advocacy after Bhopal: Environmentalism, Disaster, New Global Orders“This is an original, diverse, and scintillating collection. Researchers working on political ecology of conservation and conservation social science have not taken challenges of data justice or the political economy of data production seriously enough. We must—and this book shows us how and why.”—Dan Brockington, author of Celebrity Advocacy and International Development“As environments are reverse engineered to match the spreadsheets and management platforms in which they are tallied, the environmental politics of data control, organization, and proliferation will hugely influence ecologies and politics going forward. By putting that insight front and center, Goldstein and Nost assemble a sweeping set of essays that gaze into the sometimes-disturbing future of the planet.”—Paul Robbins, author of Political Ecology: A Critical Introduction“This volume contributes to the growing discourses around political ecological work on data and the infrastructures that sustain, produce, and exchange them. The volume is startling in both its depth and breadth of engagement with timely and important topics; it marks a significant contribution to a growing field.”—Jim Thatcher, author of Thinking Big Data in Geography: New Regimes, New Research“Throughout, the reader is plunged into the complexities of digital systems, the environments they monitor and conserve, and the limits to their governance and oversight across a variety of places and scales and sovereignties. What emerges is resolutely not an endorsement of further digitalization of nature but a recognition that digitalization is perhaps yet another set of processes in which nature is actively produced.”—Matthew W. Wilson, author of New Lines: Critical GIS and the Trouble of the MapTable of ContentsList of Illustrations List of Tables Introduction: Infrastructuring Environmental Data Jenny Goldstein and Eric Nost Part 1. Sensors, Servers, and Structures 1. Data’s Metropolis: The Physical Footprints of Data Circulation and Modern Finance Graham Pickren 2. An Emerging Satellite Ecosystem and the Changing Political Economy of Remote Sensing Luis F. Alvarez León 3. Smart Earth: Environmental Governance in a Wired World Karen Bakker and Max Ritts 4. Data, Colonialism, and the Transformation of Nature in the Pacific Northwest Anthony Levenda and Zbigniew Grabowski Part 2. Civic Science and Community-Driven Data 5. Environmental Sensing Infrastructures and Just Good Enough Data Jennifer Gabrys and Helen Pritchard 6. Collaborative Modeling as Sociotechnical Data Infrastructure in Rural Zimbabwe M. V. Eitzel, Jon Solera, K. B. Wilson, Abraham Mawere Ndlovu, Emmanuel Mhike Hove, Daniel Ndlovu, Abraham Changarara, Alice Ndlovu, Kleber Neves, Adnomore Chirindira, Oluwasola E. Omoju, Aaron C. Fisher, and André Veski 7. Citizen Scientists and Conservation in the Anthropocene: From Monitoring to Making Coral Irus Braverman 8. Data Infrastructures, Indigenous Knowledge, and Environmental Observing in the Arctic Noor Johnson, Colleen Strawhacker, and Peter Pulsifer 9. Digital Infrastructure and the Affective Nature of Value in Belize Patrick Gallagher 10. Infrastructuring Environmental Data Justice Dawn Walker, Eric Nost, Aaron Lemelin, Rebecca Lave, Lindsey Dillon, and Environmental Data and Governance Initiative (EDGI) Part 3. Governing Data, Infrastructuring Land and Resources 11. “A Poverty of Data”? Exporting the Digital Revolution to Farmers in the Global South Madeleine Fairbairn and Zenia Kish 12. Illicit Digital Environments: Monitoring and Surveilling Environmental Crime in Southeast Asia Hilary O. Faxon and Jenny Goldstein 13. Data Gaps: Penguin Science and Petrostate Formation in the Falkland Islands (Malvinas) James J. A. Blair 14. Data Structures, Indigenous Ontologies, and Hydropower in the U.S. Northwest Corrine Armistead 15. How Forest Became Data: The Remaking of Ground-Truth in Indonesia Cindy Lin Conclusion: Toward a Political Ecology of Data Rebecca Lave, Eric Nost, and Jenny Goldstein Source Acknowledgments Contributors Index
£69.70
University of Nebraska Press The Nature of Data
Book SynopsisWhen we look at some of the most pressing issues in environmental politics today, it is hard to avoid data technologies. Big data, artificial intelligence, and data dashboards all promise “revolutionary” advances in the speed and scale at which governments, corporations, conservationists, and even individuals can respond to environmental challenges. By bringing together scholars from geography, anthropology, science and technology studies, and ecology, The Nature of Data explores how the digital realm is a significant site in which environmental politics are waged. This collection as a whole makes the argument that we cannot fully understand the current conjuncture in critical, global environmental politics without understanding the role of data platforms, devices, standards, and institutions. In particular, The Nature of Data addresses the contested practices of making and maintaining data infrastructure, the imaginaries produced by data infrastruTrade Review"This book is a necessary piece to lay the groundwork for a political ecology of data and urge more research in this direction. . . . A welcome integration of digital social sciences, political ecology, critical GIS, and science and technology studies, and as such which will be of interest to scholars across these fields, but also to conservation practitioners. This collection of essays might also be useful as a methodological text for advanced graduate students."—Anne-Lise Boyer, H-Environment"Thanks to insights from ecomedia studies, environmental humanists are increasingly studying how the environment becomes digital and the digital becomes environmental. The Nature of Data ably contributes to this research."—Heather Houser, ISLE“Data may not grow on trees, but it increasingly shapes how humans know, govern, and struggle over forests—and indeed, much of the nonhuman world. The Nature of Data captures this moment empirically while advancing political ecology conceptually. An altogether stellar volume.”—Susanne Freidberg, author of Fresh: A Perishable History“In accelerating ways, environmental politics are data politics. This powerful book shows what this looks like in different settings and at different scales, persuasively calling for a new subfield focused on the political ecology of data. Extending from prior work on the delimitations and politics of environmental science, the collection draws out what environmental data can help us see, what it cuts out, and how environmental data production itself is both polluting and weighted by commercial interests.”—Kim Fortun, author of Advocacy after Bhopal: Environmentalism, Disaster, New Global Orders“This is an original, diverse, and scintillating collection. Researchers working on political ecology of conservation and conservation social science have not taken challenges of data justice or the political economy of data production seriously enough. We must—and this book shows us how and why.”—Dan Brockington, author of Celebrity Advocacy and International Development“As environments are reverse engineered to match the spreadsheets and management platforms in which they are tallied, the environmental politics of data control, organization, and proliferation will hugely influence ecologies and politics going forward. By putting that insight front and center, Goldstein and Nost assemble a sweeping set of essays that gaze into the sometimes-disturbing future of the planet.”—Paul Robbins, author of Political Ecology: A Critical Introduction“This volume contributes to the growing discourses around political ecological work on data and the infrastructures that sustain, produce, and exchange them. The volume is startling in both its depth and breadth of engagement with timely and important topics; it marks a significant contribution to a growing field.”—Jim Thatcher, author of Thinking Big Data in Geography: New Regimes, New Research“Throughout, the reader is plunged into the complexities of digital systems, the environments they monitor and conserve, and the limits to their governance and oversight across a variety of places and scales and sovereignties. What emerges is resolutely not an endorsement of further digitalization of nature but a recognition that digitalization is perhaps yet another set of processes in which nature is actively produced.”—Matthew W. Wilson, author of New Lines: Critical GIS and the Trouble of the MapTable of ContentsList of Illustrations List of Tables Introduction: Infrastructuring Environmental Data Jenny Goldstein and Eric Nost Part 1. Sensors, Servers, and Structures 1. Data’s Metropolis: The Physical Footprints of Data Circulation and Modern Finance Graham Pickren 2. An Emerging Satellite Ecosystem and the Changing Political Economy of Remote Sensing Luis F. Alvarez León 3. Smart Earth: Environmental Governance in a Wired World Karen Bakker and Max Ritts 4. Data, Colonialism, and the Transformation of Nature in the Pacific Northwest Anthony Levenda and Zbigniew Grabowski Part 2. Civic Science and Community-Driven Data 5. Environmental Sensing Infrastructures and Just Good Enough Data Jennifer Gabrys and Helen Pritchard 6. Collaborative Modeling as Sociotechnical Data Infrastructure in Rural Zimbabwe M. V. Eitzel, Jon Solera, K. B. Wilson, Abraham Mawere Ndlovu, Emmanuel Mhike Hove, Daniel Ndlovu, Abraham Changarara, Alice Ndlovu, Kleber Neves, Adnomore Chirindira, Oluwasola E. Omoju, Aaron C. Fisher, and André Veski 7. Citizen Scientists and Conservation in the Anthropocene: From Monitoring to Making Coral Irus Braverman 8. Data Infrastructures, Indigenous Knowledge, and Environmental Observing in the Arctic Noor Johnson, Colleen Strawhacker, and Peter Pulsifer 9. Digital Infrastructure and the Affective Nature of Value in Belize Patrick Gallagher 10. Infrastructuring Environmental Data Justice Dawn Walker, Eric Nost, Aaron Lemelin, Rebecca Lave, Lindsey Dillon, and Environmental Data and Governance Initiative (EDGI) Part 3. Governing Data, Infrastructuring Land and Resources 11. “A Poverty of Data”? Exporting the Digital Revolution to Farmers in the Global South Madeleine Fairbairn and Zenia Kish 12. Illicit Digital Environments: Monitoring and Surveilling Environmental Crime in Southeast Asia Hilary O. Faxon and Jenny Goldstein 13. Data Gaps: Penguin Science and Petrostate Formation in the Falkland Islands (Malvinas) James J. A. Blair 14. Data Structures, Indigenous Ontologies, and Hydropower in the U.S. Northwest Corrine Armistead 15. How Forest Became Data: The Remaking of Ground-Truth in Indonesia Cindy Lin Conclusion: Toward a Political Ecology of Data Rebecca Lave, Eric Nost, and Jenny Goldstein Source Acknowledgments Contributors Index
£21.59
Nova Science Publishers Inc Data Storage: Systems, Management & Security
Book Synopsis
£78.39
Basic Books The Rules of Contagion: Why Things Spread--And
Book Synopsis
£15.19
Basic Books The Model Thinker Lib/E: What You Need to Know to
Book Synopsis
£89.24
Basic Books The Model Thinker: What You Need to Know to Make
Book Synopsis
£30.00
ESRI Press The Esri Guide to GIS Analysis, Volume 3:
Book SynopsisThe third volume in the Esri Guide to GIS Analysis series, Modeling Suitability, Movement, and Interaction describes practical applications of modeling concepts in a geographic information system (GIS). Modeling allows users to explore different scenarios and the impacts of various options, before making a decision.This book covers a broad range of methods for spatial interaction, site selection, routing, and scheduling, and explains the theory behind them so users can better interpret the analysis results. It also describes how a particular method is implemented within a GIS. With full-color maps and illustrations and sample applications, this book will help students studying GIS and professional GIS analysts better use models to evaluate locations and analyze movementTable of ContentsChapter 1 Introducing GIS modeling The GIS modeling process Define the goal of the analysis Define the criteria Collect the data Run the model Verify the results Modify and re-run the model Document the analysis Display and apply the results Modeling and GIS data Spatial data types Attribute data Accounting for spatial bias Geographic scale Data quality References and further reading Chapter 2 Finding suitable locations Designing a Boolean suitability model Evaluating locations Identifying potential locations References and further reading Chapter 3 Rating suitable locations Designing a suitability model to rate locations Rating locations using weighted overlay Rating locations using fuzzy overlay References and further reading Chapter 4 Predicting favorable locations Designing a model to predict favorable locations Predicting using known occurrences References and further reading Chapter 5 Modeling paths and corridors Designing a path model Modeling a path over a network Modeling an overland path References and further reading Chapter 6 Modeling interaction Designing a model of interaction Allocating demand to facilities Modeling travel to facilities References and further reading
£37.04
Holy Macro! Books Supercharge Excel
Book SynopsisData analysis expressions (DAX) is the formula language of Power Pivot. Learning the DAX language is key to empower Excel users so they can take advantage of these new Business Intelligence (BI) capabilities. This volume clearly explains the concepts of Power Pivot while at the same time offering hands-on practice to engage the reader and help new knowledge stick. This second edition has been updated for the Excel 2016 user interface while still providing a bridge for readers wanting to learn DAX in the Excel environment and then transfer their new DAX skills across to Power BI.
£22.91
Holy Macro! Books Supercharge Power BI: Power BI is Better When You
Book SynopsisData analysis expressions (DAX) is the formula language of Power BI. Learning the DAX language is key to empower Power BI users so they can take advantage of these new Business Intelligence (BI) capabilities. This third edition has been updated for the new Power BI Ribbon interface while still providing a bridge for readers wanting to learn DAX in the Power BI, Power Pivot, or Excel.
£26.31
Manning Publications Kafka in Action
Book SynopsisKafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka's most common use cases, ranging from simple logging through managing streaming data systems for message routing, analytics, and more. In systems that handle big data, streaming data, or fast data, it's important to get your data pipelines right. Apache Kafka is a wicked-fast distributed streaming platform that operates as more than just a persistent log or a flexible message queue. Key Features · Understanding Kafka's concepts · Implementing Kafka as a message queue · Setting up and executing basic ETL tasks · Recording and consuming streaming data · Working with Kafka producers and consumers from Java applications · Using Kafka as part of a large data project team · Performing Kafka developer and admin tasks Written for intermediate Java developers or data engineers. No prior knowledge of Kafka is required. About the technology Apache Kafka is a distributed streaming platform for logging and streaming data between services or applications. With Kafka, it's easy to build applications that can act on or react to data streams as they flow through your system. Operational data monitoring, large scale message processing, website activity tracking, log aggregation, and more are all possible with Kafka. Dylan Scott is a software developer with over ten years of experience in Java and Perl. His experience includes implementing Kafka as a messaging system for a large data migration, and he uses Kafka in his work in the insurance industry.
£25.49
Manning Publications Graph Databases in Action
Book SynopsisGraph Databases in Action teaches readers everything they need to know to begin building and running applications powered by graph databases. Right off the bat, seasoned graph database experts introduce readers to just enough graph theory, the graph database ecosystem, and a variety of datastores. They also explore modelling basics in action with real-world examples, then go hands-on with querying, coding traversals, parsing results, and other essential tasks as readers build their own graph-backed social network app complete with a recommendation engine! Key Features · Graph database fundamentals · An overview of the graph database ecosystem · Relational vs. graph database modelling · Querying graphs using Gremlin · Real-world common graph use cases For readers with basic Java and application development skills building in RDBMS systems such as Oracle, SQL Server, MySQL, and Postgres. No experience with graph databases is required. About the technology Graph databases store interconnected data in a more natural form, making them superior tools for representing data with rich relationships. Unlike in relational database management systems (RDBMS), where a more rigid view of data connections results in the loss of valuable insights, in graph databases, data connections are first priority. Dave Bechberger has extensive experience using graph databases as a product architect and a consultant. He’s spent his career leveraging cutting-edge technologies to build software in complex data domains such as bioinformatics, oil and gas, and supply chain management. He’s an active member of the graph community and has presented on a wide variety of graph-related topics at national and international conferences. Josh Perryman is technologist with over two decades of diverse experience building and maintaining complex systems, including high performance computing (HPC) environments. Since 2014 he has focused on graph databases, especially in distributed or big data environments, and he regularly blogs and speaks at conferences about graph databases.
£35.99
Technics Publications LLC Data Modeling Master Class Training Manual: Steve
Book Synopsis
£149.24
Technics Publications LLC Object-Role Modeling Workbook: Data Modeling
Book SynopsisObject-Role Modeling (ORM) is a fact-based approach to data modelling that expresses the information requirements of any business domain simply in terms of objects that play roles in relationships. All facts of interest are treated as instances of attribute-free structures known as fact types, where the relationship may be unary (eg: Person smokes), binary (eg: Person was born on Date), ternary (eg: Customer bought Product on Date), or longer. Fact types facilitate natural expression, are easy to populate with examples for validation purposes, and have greater semantic stability than attribute-based structures such as those used in Entity Relationship Modeling (ER) or the Unified Modeling Language (UML). All relevant facts, constraints and derivation rules are expressed in controlled natural language sentences that are intelligible to users in the business domain being modelled. This allows ORM data models to be validated by business domain experts who are unfamiliar with ORM''s graphical notation. For the data modeller, ORM''s graphical notation covers a much wider range of constraints than can be expressed in industrial ER or UML class diagrams, and thus allows rich visualisation of the underlying semantics. Written as a sequel to the author''s previous book "Object-Role Modeling Fundamentals", this book briefly reviews the fundamentals of ORM, and then discusses additional topics such as model reports generation, vocabulary glossaries, relational mapping options, annotated relational schemas, schema optimisation, and data modelling patterns. Written in easy-to-understand language, it illustrates each topic with simple examples, and explains how to use the freeware NORMA tool to implement the ideas discussed. The book also includes many practical exercises to promote expertise in the techniques covered, with answers provided to all the exercise questions.
£32.79
Technics Publications LLC NoSQL & SQL Data Modeling: Bringing Together
Book SynopsisHow do we design for data when traditional design techniques cannot extend to new database technologies? In this era of big data and the Internet of Things, it is essential that we have the tools we need to understand the data coming to us faster than ever before, and to design databases and data processing systems that can adapt easily to ever-changing data schemas and ever-changing business requirements. There must be no intellectual disconnect between data and the software that manages it. It must be possible to extract meaning and knowledge from data to drive artificial intelligence applications. Novel NoSQL data organization techniques must be used side-by-side with traditional SQL databases. Are existing data modeling techniques ready for all of this? The Concept and Object Modeling Notation (COMN) is able to cover the full spectrum of analysis and design. A single COMN model can represent the objects and concepts in the problem space, logical data design, and concrete NoSQL and SQL document, key-value, columnar, and relational database implementations. COMN models enable an unprecedented level of traceability of requirements to implementation. COMN models can also represent the static structure of software and the predicates that represent the patterns of meaning in databases. This book will teach you: the simple and familiar graphical notation of COMN with its three basic shapes and four line styles; how to think about objects, concepts, types, and classes in the real world, using the ordinary meanings of English words that arent tangled with confused techno-speak; how to express logical data designs that are freer from implementation considerations than is possible in any other notation; how to understand key-value, document, columnar, and table-oriented database designs in logical and physical terms; how to use COMN to specify physical database implementations in any NoSQL or SQL database with the precision necessary for model-driven development. A quick reference guide to COMN is included in an appendix. The full notation reference is available at http://www.tewdur.com/
£32.79
Nova Science Publishers Inc Soft Computing: Developments, Methods &
Book Synopsis
£148.79
BCS Learning & Development Limited Principles of Data Management: Facilitating
Book SynopsisData is a valuable corporate asset and its effective management is vital to an organisation’s success and survival. With this book you will learn to master the key principles of data management and use them to implement best practices in your organization. This professional guide covers all the key areas of data management, including database development and corporate data modelling. It is business-focused, providing the knowledge and techniques required to successfully implement the data management function. This fully updated new edition provides new chapters on the most important data topics such as big data, artificial intelligence, linked data and concept systems. Principles of Data Management is fully aligned with syllabus for the BCS Professional Certificate in Data Management Essentials, making this the go-to text to unlocking the value of your data. Ideal for business managers and all involved in the development of information systems as well as data management professionals Comprehensive and descriptive view of data management Suitable for all levels, from beginners to advanced learners Must-read for anyone involved in the development of systems to manage data Trade ReviewThis book is an excellent guide to understanding data management theory and techniques. It works at all levels: from beginner to advanced, and from reference source to the practicalities of implementation. I would highly recommend to anyone wanting to get to grips with data management, regardless of experience in the field. -- Ian Wallis, Managing Director, Data Strategists LtdKeith has developed a broad and thorough understanding of all aspects of data management over many years, so is without doubt one of the authorities on data management. This updated book includes reference to a number of new techniques as well as refining existing guidance on data modelling and database structures. Keith clearly explains both the importance of planning and analysis of databases and repositories and an explanation of key techniques to achieve this. A ‘must buy’ for the bookshelf of any data management practitioner. -- Julian Schwarzenbach, Chair of the BCS Data Management Specialist GroupThis book provides a comprehensive and descriptive view of data management within a database setting. This is a must read for anyone involved in the development of systems to manage data. This book is as useful as it is interesting. It covers everything you need to know about getting the most out of your data management processes and architecture. -- Ian Rush, Data & Process Advantage LtdTable of ContentsPart 1: Preliminaries Chapter 1 Data and the enterprise Chapter 2 Databases and their development Chapter 3 What is data management? Part 2: Data Administration Chapter 4 Corporate data modelling Chapter 5 Data definition and naming Chapter 6 Metadata Chapter 7 Data quality Chapter 8 Data accessibility Chapter 9 Master data management Part 3: Database and Repository Administration Chapter 10 Database administration Chapter 11 Repository administration Part 4: The Data Management Environment Chapter 12 The use of packaged application software Chapter 13 Distributed data and databases Chapter 14 Business intelligence Chapter 15 Object orientation Chapter 16 Multimedia Chapter 17 Integrating data and web technology Chapter 18 Linked data Chapter 19 Concept systems Chapter 20 Big data and artificial intelligence Appendices Appendix A Comparison of data modelling notations Appendix B Generic data models Appendix C HTML and XML Appendix D Techniques and skills for data management Appendix E Data strategy Appendix F International standards for data management Appendix G The BCS Data Management Essentials syllabus
£33.24
CABI Publishing Big Data’s Big Potential in Developing Economies:
Book SynopsisBig data involves the use of sophisticated analytics to make decisions based on large-scale data inputs. It is set to transform agriculture, environmental protection and healthcare in developing countries. This book critically evaluates the developing big data industry and market in these countries and gives an overview of the determinants, performance and impacts. It provides a detailed analysis of technology creation, technology infrastructures and human skills required to utilize big data while discussing novel applications and business models that make use of it to overcome healthcare barriers. The book also offers an analysis of big data's potential to improve environmental monitoring and protection where it is likely to have far-reaching and profound impacts on the agricultural sector. A key question addressed is how gains in agricultural productivity associated with big data will benefit smallholder farmers relative to global multinationals in that sector. The book also probes big data's roles in the creation of markets that can improve the welfare of smallholder farmers. Special consideration is given to big data-led transformation of the financial industry and discusses how the transformation can increase small-holder farmers' access to finance by changing the way lenders assess creditworthiness of potential borrowers. It also takes a look at data privacy and security issues facing smallholder farmers and reviews differences in such issues in industrialized and developing countries. The key ideas, concepts and theories presented are explored, illustrated and contrasted through in-depth case studies of developing world-based big data companies, and deployment and utilization of big data in agriculture, environmental protection and healthcare.Table of ContentsChapter 1: Big Data in Developing Countries: Current Status, Opportunities and Challenges Chapter 2: Big Data Ecosystem in Developing Countries Chapter 3: Big Data in Environmental Protection and Resources Conservation Chapter 4: Big Data in Healthcare Delivery and Outcomes Chapter 5: Big Data in Agriculture Chapter 6: Big Data’s Roles in Increasing Smallholder Farmers’ Access to Finance Chapter 7: Data Privacy and Security Issues Facing Smallholder Farmers and Poor Communities in Developing Countries Chapter 8: Lessons Learned, Implications and the Way Forward
£89.09
Packt Publishing Limited Python: Advanced Predictive Analytics: Gain
Book SynopsisGain practical insights by exploiting data in your business to build advanced predictive modeling applications Key Features A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Learn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Master open source Python tools to build sophisticated predictive models Book Description Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. This book is your guide to getting started with predictive analytics using Python. You'll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications. Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates explains how these methods work. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring to life the insights of predictive modeling. Finally, you will learn best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. The course provides you with highly practical content from the following Packt books: 1. Learning Predictive Analytics with Python 2. Mastering Predictive Analytics with Python What you will learn Understand the statistical and mathematical concepts behind predictive analytics algorithms and implement them using Python libraries Get to know various methods for importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and NumPy Master the use of Python notebooks for exploratory data analysis and rapid prototyping Get to grips with applying regression, classification, clustering, and deep learning algorithms Discover advanced methods to analyze structured and unstructured data Visualize the performance of models and the insights they produce Ensure the robustness of your analytic applications by mastering the best practices of predictive analysis Who this book is for This book is designed for business analysts, BI analysts, data scientists, or junior level data analysts who are ready to move on from a conceptual understanding of advanced analytics and become an expert in designing and building advanced analytics solutions using Python. If you are familiar with coding in Python (or some other programming/statistical/scripting language) but have never used or read about predictive analytics algorithms, this book will also help you.Table of ContentsTable of Contents Module 1 Module 2
£75.04
Packt Publishing Limited Become a Python Data Analyst: Perform exploratory
Book SynopsisEnhance your data analysis and predictive modeling skills using popular Python toolsKey Features Cover all fundamental libraries for operation and manipulation of Python for data analysis Implement real-world datasets to perform predictive analytics with Python Access modern data analysis techniques and detailed code with scikit-learn and SciPy Book DescriptionPython is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations.Become a Python Data Analyst introduces Python’s most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations.In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques.By the end of this book, you will have hands-on experience performing data analysis with Python.What you will learn Explore important Python libraries and learn to install Anaconda distribution Understand the basics of NumPy Produce informative and useful visualizations for analyzing data Perform common statistical calculations Build predictive models and understand the principles of predictive analytics Who this book is forBecome a Python Data Analyst is for entry-level data analysts, data engineers, and BI professionals who want to make complete use of Python tools for performing efficient data analysis. Prior knowledge of Python programming is necessary to understand the concepts covered in this bookTable of ContentsTable of Contents The Anaconda Distribution and Jupyter Notebook Vectorizing Operations with Numpy Pandas: Everyone’s Favorite Data Analysis Library Visualization and Exploratory Data Analysis Statistical Computing with Python Introduction to Predictive Analytics Models
£18.99
Packt Publishing Limited Data Engineering with Scala and Spark: Build
Book SynopsisTake your data engineering skills to the next level by learning how to utilize Scala and functional programming to create continuous and scheduled pipelines that ingest, transform, and aggregate data Key Features Transform data into a clean and trusted source of information for your organization using Scala Build streaming and batch-processing pipelines with step-by-step explanations Implement and orchestrate your pipelines by following CI/CD best practices and test-driven development (TDD) Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMost data engineers know that performance issues in a distributed computing environment can easily lead to issues impacting the overall efficiency and effectiveness of data engineering tasks. While Python remains a popular choice for data engineering due to its ease of use, Scala shines in scenarios where the performance of distributed data processing is paramount. This book will teach you how to leverage the Scala programming language on the Spark framework and use the latest cloud technologies to build continuous and triggered data pipelines. You’ll do this by setting up a data engineering environment for local development and scalable distributed cloud deployments using data engineering best practices, test-driven development, and CI/CD. You’ll also get to grips with DataFrame API, Dataset API, and Spark SQL API and its use. Data profiling and quality in Scala will also be covered, alongside techniques for orchestrating and performance tuning your end-to-end pipelines to deliver data to your end users. By the end of this book, you will be able to build streaming and batch data pipelines using Scala while following software engineering best practices.What you will learn Set up your development environment to build pipelines in Scala Get to grips with polymorphic functions, type parameterization, and Scala implicits Use Spark DataFrames, Datasets, and Spark SQL with Scala Read and write data to object stores Profile and clean your data using Deequ Performance tune your data pipelines using Scala Who this book is forThis book is for data engineers who have experience in working with data and want to understand how to transform raw data into a clean, trusted, and valuable source of information for their organization using Scala and the latest cloud technologies.Table of ContentsTable of Contents Scala Essentials for Data Engineers Environment Setup An Introduction to Apache Spark and Its APIs – DataFrame, Dataset, and Spark SQL Working with Databases Object Stores and Data Lakes Understanding Data Transformation Data Profiling and Data Quality Test-Driven Development, Code Health, and Maintainability CI/CD with GitHub Data Pipeline Orchestration Performance Tuning Building Batch Pipelines Using Spark and Scala Building Streaming Pipelines Using Spark and Scala
£32.29
Packt Publishing Limited Alteryx Designer Cookbook: Over 60 recipes to
Book SynopsisStreamline your workflow, transform raw data into actionable insights, and use Alteryx Designer to shape, design, and visualize data Key Features Acquire the skills necessary to perform analytics operations like an expert Discover hidden trends and insights in your data from various sources to make accurate predictions Reduce the time and effort required to derive insights from your data Purchase of the print or Kindle book includes a free eBook in the PDF format Book DescriptionAlteryx allows you to create data manipulation and analytic workflows with a simple, easy-to-use, code-free UI, and perform fast-executing workflows, offering multiple ways to achieve the same results. The Alteryx Designer Cookbook is a comprehensive guide to maximizing your Alteryx skills and determining the best ways to perform data operations. This book's recipes will guide you through an analyst's complete journey, covering all aspects of the data life cycle. The first set of chapters will teach you how to read data from various sources to obtain reports and pass it through the required adjustment operations for analysis. After an explanation of the Alteryx platform components with a particular focus on Alteryx Designer, you’ll be taken on a tour of what and how you can accomplish by using this tool. Along the way, you’ll learn best practices and design patterns. The book also covers real-world examples to help you apply your understanding of the features in Alteryx to practical scenarios. By the end of this book, you’ll have enhanced your proficiency with Alteryx Designer and an improved ability to execute tasks within the tool efficiently.What you will learn Speed up the cleansing, data preparing, and shaping process Perform operations and transformations on the data to suit your needs Blend different types of data sources for analysis Pivot and un-pivot the data for easy manipulation Perform aggregations and calculations on the data Encapsulate reusable logic into macros Develop high-quality, data-driven reports to improve consistency Who this book is forThis book is for data analysts, data professionals, and business intelligence professionals seeking to harness the full potential of the tool. A basic understanding of Alteryx Designer and Alteryx terminology, including macros, apps, and workflows, is all you need to get started with this book.Table of ContentsTable of Contents Input data from files Working with databases Data Preparation Data Transformations Data Parsing Grouping Data Blending and Merging data Aggregations Dynamic Operations/ Tools Macros and Apps Downloads, APIs & Web Services Developer options Reporting with Alteryx Outputting Data
£48.59
Pearson Education Limited BTEC Level 3 National IT Student Book 2
Book SynopsisResources designed to support learners of the 2010 BTEC Level 3 National IT specification*. Extensive unit coverage: Student Book 2 covers 14 units including all the mandatory units, giving learners the breadth to tailor the course to their needs and interests, when combined with Student Book 1. Functional Skills and Personal Learning and Thinking Skills are embedded in activities throughout the book. WorkSpace case studies take learners into the real world of work, showing them how they can apply their knowledge in a real-life context.
£34.59
ISTE Ltd and John Wiley & Sons Inc From Big Data to Smart Data
Book SynopsisA 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.Table of ContentsPREFACE ix LIST OF FIGURES AND TABLES xiii INTRODUCTION xv CHAPTER 1. WHAT IS BIG DATA? 1 1.1. The four “V”s characterizing Big Data 3 1.1.1. V for “Volume” 3 1.1.2. V for “Variety” 4 1.1.3. V for “Velocity” 8 1.1.4. V for “Value”, associated with Smart Data 9 1.2. The technology that supports Big Data 10 CHAPTER 2. WHAT IS SMART DATA? 13 2.1. How can we define it? 13 2.1.1. More formal integration into business processes 13 2.1.2. A stronger relationship with transaction solutions 14 2.1.3. The mobility and the temporality of information 15 2.2. The structural dimension 17 2.2.1. The objectives of a BICC 17 2.3. The closed loop between Big Data and Smart Data 18 CHAPTER 3. ZERO LATENCY ORGANIZATION 21 3.1. From Big Data to Smart Data for a zero latency organization 21 3.2. Three types of latency 21 3.2.1. Latency linked to data 21 3.2.2. Latency linked to analytical processes 22 3.2.3. Latency linked to decisionmaking processes 23 3.2.4. Action latency 23 CHAPTER 4. SUMMARY BY EXAMPLE 25 4.1. Example 1: date/product/price recommendation 26 4.1.1. Steps “1” and “2” 28 4.1.2. Steps “3” and “4”: enter the world of “Smart Data” 29 4.1.3. Step “5”: the presentation phase 29 4.1.4. Step “6”: the “Holy Grail” (the purchase) 30 4.1.5. Step “7”: Smart Data 30 4.2. Example 2: yield/revenue management (rate controls) 31 4.2.1. How it works: an explanation based on the Tetris principle (see Figure 4.4) 35 4.3. Example 3: optimization of operational performance 38 4.3.1. General department (top management) 42 4.3.2. Operations departments (middle management) 42 4.3.3. Operations management (and operational players) 43 CONCLUSION 47 BIBLIOGRAPHY 51 GLOSSARY 53 INDEX 57
£125.06
Packt Publishing Limited Data Visualization a successful design process
Book SynopsisA comprehensive yet quick guide to the best approaches to designing data visualizations, with real examples and illustrative diagrams. Whatever the desired outcome ensure success by following this expert design process. This book is for anyone who has responsibility for, or is interested in trying to find innovative and effective ways to visually analyze and communicate data. There is no skill, no knowledge and no role-based pre-requisites or expectations of anyone reading this book.
£22.79
Technics Publications LLC Data Modeling Master Class Training Manual: Steve
Book Synopsis
£149.24
Columbia Books on Architecture and the City Preservation and the New Data Landscape
Book SynopsisOver the past fifty years, preservation policy has evolved very little, despite escalating accusations that landmarking and historic districting can inhibit affordable housing, economic development, and socioeconomic diversity. The potential to understand these dynamics and effect positive change is hindered by a lack of data and evidence-based research to better understand these impacts. One of the biggest barriers to preservation research has been the lack of data sets that can be used for geospatial, evidence-based, and longitudinal analyses.This first book in the series Issues in Preservation Policy explores the ways that enhancing the collection, accuracy, and management of data can serve a critical role in identifying vulnerable neighborhoods, understanding the role of older buildings in economic vitality and community resilience, planning sustainable growth, and more. For preservation to play a dynamic role in sustainable development and social inclusion, policy must evolve beyond designation and design regulation and use evidence-based research to confront new realities in the management of urban environments and their communities.
£30.76
Springer Nature Switzerland AG Handbook of Image Processing and Computer Vision:
Book SynopsisAcross three volumes, the Handbook of Image Processing and Computer Vision presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The authoritative insights presented within cover all aspects of the sensory subsystem required by an intelligent system to perceive the environment and act autonomously. Volume 1 (From Energy to Image) examines the formation, properties, and enhancement of a digital image.Topics and features:• Describes the fundamental processes in the field of artificial vision that enable the formation of digital images from light energy• Covers light propagation, color perception, optical systems, and the analog-to-digital conversion of the signal• Discusses the information recorded in a digital image, and the image processing algorithms that can improve the visual qualities of the image• Reviews boundary extraction algorithms, key linear and geometric transformations, and techniques for image restoration• Presents a selection of different image segmentation algorithms, and of widely-used algorithms for the automatic detection of points of interest• Examines important algorithms for object recognition, texture analysis, 3D reconstruction, motion analysis, and camera calibration• Provides an introduction to four significant types of neural network, namely RBF, SOM, Hopfield, and deep neural networksThis all-encompassing survey offers a complete reference for all students, researchers, and practitioners involved in developing intelligent machine vision systems. The work is also an invaluable resource for professionals within the IT/software and electronics industries involved in machine vision, imaging, and artificial intelligence.Dr. Cosimo Distante is a Research Scientist in Computer Vision and Pattern Recognition in the Institute of Applied Sciences and Intelligent Systems (ISAI) at the Italian National Research Council (CNR). Dr. Arcangelo Distante is a researcher and the former Director of the Institute of Intelligent Systems for Automation (ISSIA) at the CNR. His research interests are in the fields of Computer Vision, Pattern Recognition, Machine Learning, and Neural Computation.Table of ContentsImage Formation Process Radiometric Model Color Optical System Digitization and Image Display Properties of the Digital Image Data Organization Representation and Description of Forms Image Enhancement Techniques
£161.99
De Gruyter Data Fabric Architectures: Web-Driven
Book SynopsisThe immense increase on the size and type of real time data generated across various edge computing platform results in unstructured databases and data silos. This edited book gathers together an international set of researchers to investigate the possibilities offered by data-fabric solutions; the volume focuses in particular on data architectures and on semantic changes in future data landscapes.
£105.00
Springer Fachmedien Wiesbaden Einführung in Evolutionäre Algorithmen:
Book SynopsisDieses Lehrbuch aus dem KI-Themenfeld richtet sich an Wirtschaftsinformatiker und Informatiker, ferner an Ingenieure und OR-Spezialisten. Es bietet eine umfassende methodisch orientierte Einführung in das Optimieren mit Evolutionären Algorithmen. Dazu gehören vor allem Genetische Algorithmen, Evolutionsstrategien, Genetische bzw. Evolutionäre Programmierung. Wichtige Ergebnisse der Theorie werden in gut verständlicher Form wiedergegeben. Zahlreiche Abbildungen und Beispiele sowie Hinweise auf Quellen im Internet und Testdaten ergänzen den Text. Das Buch kann als Grundlage zur Entwicklung eigener Anwendungen dienen oder als begleitender Text für Lehrveranstaltungen.Table of ContentsThematische Einordnung - Relevante Grundelemente der Evolutionstheorie - Genetische Algorithmen - Genetische Programmierung - Evolutionsstrategien - Evolutionäre Programmierung - Lernende Classifier Systeme - Kombinationsmöglichkeiten mit Neuronalen Netzen und der Fuzzy Set Theorie - Vergleich und Beurteilung von Evolutionären Algorithmen - Zahlreiche Abbildungen und Beispiele - Umfangreiche Literaturhinweise - Verweise auf Quellen im Internet - Testdaten - Index
£34.19
Springer Fachmedien Wiesbaden Formale Sprachen: Endliche Automaten,
Book SynopsisDieses Lehrbuch mit detailliert ausgearbeiteten Erklärungen und auf die Zielsetzungen fein abgestimmtem Training bietet einen einfachen Einstieg in die Theorie der formalen Sprachen. Es eignet sich gut für den Unterricht und das Selbststudium. Neben Gymnasiasten und Studienanfängern an Hochschulen richtet es sich auch an Lehramtsstudierende, insbesondere wenn sie sich mit der praktischen Umsetzung der Fachdidaktik für die Unterrichtsvorbereitung beschäftigen.Inhaltlich liegt der Fokus auf endlichen Automaten zur Systemsteuerung und zur Mustererkennung in Texten sowie auf Grammatiken zur Beschreibung von Programmiersprachen. Weiter werden erste Schritte im Compilerbau (lexikalische und syntaktische Analyse) unternommen.Die Leserinnen und Leser werden zur Bearbeitung von Projekten zur Darstellung und Analyse einfacher Programmiersprachen eingeladen.Table of ContentsAlphabete, Wörter und Sprachen - Das Modell der endlichen Automaten - Entwurf von endlichen Automaten - Projekt "Steuerungsautomaten" - Induktionsbeweise der Korrektheit - Simulation und modularer Entwurf endlicher Automaten - Größe endlicher Automaten und Nichtexistenzbeweise - Automaten mit Ausgabe und lexikalische Analyse - Kontextfreie Grammatiken - Syntaxanalyse von Programmen
£35.99
Springer Fachmedien Wiesbaden Ordnungen und Verbände: Grundlagen,
Book SynopsisDas Lehrbuch stellt eine grundlegende Einführung in die mathematische Theorie der geordneten Mengen und Verbände dar. Neben wichtigen Begriffen werden allgemeine Vorgehensweisen und Beweistechniken demonstriert, die für dieses Gebiet typisch sind. Auch werden eine Reihe von Anwendungen diskutiert, insbesondere aus der Informatik, wie logische Schaltungen, Semantik von Programmiersprachen und die Untersuchung von Kausalität in verteilten Systemen.Table of ContentsMathematische Grundlagen - Verbände und Ordnungen - Einige wichtige Verbandsklassen - Fixpunkttheorie mit Anwendungen - Vervollständigung und Darstellung mittels Vervollständigung - Wohlgeordnete Mengen und das Auswahlaxiom - Einige Informatik-Anwendungen von Ordnungen und Verbänden
£34.19
Springer Fachmedien Wiesbaden SQL & NoSQL Databases: Models, Languages,
Book SynopsisThis book offers a comprehensive introduction to relational (SQL) and non-relational (NoSQL) databases. The authors thoroughly review the current state of database tools and techniques, and examine coming innovations. The book opens with a broad look at data management, including an overview of information systems and databases, and an explanation of contemporary database types: SQL and NoSQL databases, and their respective management systems The nature and uses of Big Data A high-level view of the organization of data management Data Modeling and Consistency Chapter-length treatment is afforded Data Modeling in both relational and graph databases, including enterprise-wide data architecture, and formulas for database design. Coverage of languages extends from an overview of operators, to SQL and and QBE (Query by Example), to integrity constraints and more. A full chapter probes the challenges of Ensuring Data Consistency, covering: Multi-User Operation Troubleshooting Consistency in Massive Distributed Data Comparison of the ACID and BASE consistency models, and more System Architecture also gets from its own chapter, which explores Processing of Homogeneous and Heterogeneous Data; Storage and Access Structures; Multi-dimensional Data Structures and Parallel Processing with MapReduce, among other topics. Post-Relational and NoSQL Databases The chapter on post-relational databases discusses the limits of SQL – and what lies beyond, including Multi-Dimensional Databases, Knowledge Bases and and Fuzzy Databases. A final chapter covers NoSQL Databases, along with Development of Non-Relational Technologies, Key-Value, Column-Family and Document Stores XML Databases and Graphic Databases, and more The book includes more than 100 tables, examples and illustrations, and each chapter offers a list of resources for further reading. SQL & NoSQL Databases conveys the strengths and weaknesses of relational and non-relational approaches, and shows how to undertake development for big data applications. The book benefits readers including students and practitioners working across the broad field of applied information technology.This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland.Table of ContentsData Management - Data Modeling - Database Languages - Ensuring Data Consistency - System Architecture - Post-Relational Databases - NoSQL Databases
£40.49
Springer Fachmedien Wiesbaden Algorithmen und Datenstrukturen
Book SynopsisStatt der üblichen theoretischen Zugangs vermittelt dieses Lehrbuch Algorithmen und Datenstrukturen durch die Geschichte einer jungen Informatikerin. Der Stoff einer traditionellen Einführungsveranstaltung Informatik wird so ausgehend von der praktischen Anwendung lebendig und mit viel Spaß vermittelt. So schlägt das Buch eine Brücke von Alltagserfahrungen zu den Konzepten von Datenstrukturen und Algorithmen. Table of ContentsEin Anwendungsbeispiel - Machbarkeit und Effizienz - Einfache Ansätze - Verbesserung durch mehr Struktur - Gierige Algorithmen - Kleinster Schaden im Worst-Case - Teile und Beherrsche - Dynamisches Programmieren - Direkter Zugriff - Prioritätswarteschlangen - Extern gespeicherte Daten - Selbstorganisation - Zusammenfassung
£29.99
BPB Publications Cloud Data Architectures Demystified: Gain the
Book Synopsis
£29.92
Amsterdam University Press Open Data and the Knowledge Society
Book SynopsisWhile there is a lot of talk about how we now live in a knowledge society, the reality has been less impressive: We have yet to truly transition to a knowledge society-in part, this book argues, because discussion mostly focuses on a knowledge economy and information society rather than on ways to mobilise to create an actual knowledge society. That all may change, however, with the rise of open data and big data. This book considers the role of the open data movement in fostering transformation, showing that at the heart of any successful mobilisation will be an emerging open data ecosystem and new ways for societal actors to effectively produce and use data.Table of ContentsChapter One: Introduction Chapter Two: Defining a 'Knowledge Society' Chapter Three: Visions of Open Data Chapter Four: Mobilizing Open Data Chapter Five: Institutions in the Data Ecosystem: Actors in the Public Knowledge Domain and in Private Data Companies Chapter Six: Mobilizing Data: Scientific Disciplines, Scientific Practice, and Making Research Data Open Chapter Seven: Mobilizing Data: Environmental Data, Technical and Governance Issues Chapter Eight: Navigating Legal and Ethical Regulatory Frameworks Chapter Nine: Big Data, Open Data, and the Commercial Sector
£35.10
World Scientific Publishing Co Pte Ltd Automated Database Applications Testing:
Book SynopsisThis book introduces SpecDB, an intelligent database created to represent and host software specifications in a machine-readable format, based on the principles of artificial intelligence and unit testing database operations. SpecDB is demonstrated via two automated intelligent tools. The first automatically generates database constraints from a rule-base in SpecDB. The second is a reverse engineering tool that logs the actual execution of the program from the code.Table of ContentsSpecDB: A Database Design for Software Specifications; Representing Formal Specifications in SpecDB: A Translation Algorithm; An Automated Constraint Generator; A Reverse Engineering Testing Tool; Enhancing Other Testing Tools Using SpecDB; Conclusion for Future Work.
£80.75
World Scientific Publishing Co Pte Ltd Pattern Recognition And Big Data
Book SynopsisContaining twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications.Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.
£247.50
Independently Published ChatGPT on Physics: Exploring the Foundations and
Book Synopsis
£15.79
Pragmatic Programmers Vector Search with JavaScript
£22.09
