Big Data By Examples Using Matlab
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Big Data And Deep Learning Examples With Matlab
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Author : CESAR PEREZ LOPEZ
language : en
Publisher: CESAR PEREZ
Release Date : 2020-05-31
Big Data And Deep Learning Examples With Matlab written by CESAR PEREZ LOPEZ and has been published by CESAR PEREZ this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-31 with Computers categories.
Big Data Analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. With today's technology, it's possible to analyze your data and get answers from it almost immediately - an effort that's slower and less efficient with more traditional business intelligence solutions. Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high level abstractions in data. Various deep learning architectures such as deep neural networks, convolutional deep neural networks, deep belief networks and recurrent neural networks have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks.Deep learning has been characterized as a buzzword, or a rebranding of neural networks. This book deeps in big data and deep learning techniques
Big Data Analytics Neural Networks Applications Examples With Matlab
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Author : CESAR PEREZ LOPEZ
language : en
Publisher: CESAR PEREZ
Release Date : 2020-05-31
Big Data Analytics Neural Networks Applications Examples With Matlab written by CESAR PEREZ LOPEZ and has been published by CESAR PEREZ this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-31 with Computers categories.
MATLAB has the tool Neural Network Toolbox (Deep Learning Toolbox since release 18) that provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control. The toolbox includes convolutional neural network and autoencoder deep learning algorithms for image classification and feature learning tasks. To speed up training of large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox. This book develops neural network applications using MATLAB.
Big Data By Examples Using Matlab
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Author : G. Peck
language : en
Publisher:
Release Date : 2017-03-12
Big Data By Examples Using Matlab written by G. Peck and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-12 with categories.
Big data is a term that describes the large volume of data - both structured and unstructured - that inundates a business on a day-to-day basis. But it's not the amount of data that's important. It's what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves. The most important characteristics of the big data are:Volume. Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to-machine data. In the past, storing it would've been a problem - but new technologies (such as Hadoop) have eased the burden.Velocity. Data streams in at an unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time.Variety. Data comes in all types of formats - from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions.Variability. In addition to the increasing velocities and varieties of data, data flows can be highly inconsistent with periodic peaks. Is something trending in social media? Daily, seasonal and event-triggered peak data loads can be challenging to manage. Even more so with unstructured data.Complexity. Today's data comes from multiple sources, which makes it difficult to link, match, cleanse and transform data across systems. However, it's necessary to connect and correlate relationships, hierarchies and multiple data linkages or your data can quickly spiral out of control.
Planning For Big Data
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Author : Edd Wilder-James
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-03-12
Planning For Big Data written by Edd Wilder-James and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-12 with Computers categories.
In an age where everything is measurable, understanding big data is an essential. From creating new data-driven products through to increasing operational efficiency, big data has the potential to make your organization both more competitive and more innovative. As this emerging field transitions from the bleeding edge to enterprise infrastructure, it's vital to understand not only the technologies involved, but the organizational and cultural demands of being data-driven. Written by O'Reilly Radar's experts on big data, this anthology describes: The broad industry changes heralded by the big data era What big data is, what it means to your business, and how to start solving data problems The software that makes up the Hadoop big data stack, and the major enterprise vendors' Hadoop solutions The landscape of NoSQL databases and their relative merits How visualization plays an important part in data work
Data Science And Big Data Computing
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Author : Zaigham Mahmood
language : en
Publisher: Springer
Release Date : 2016-07-05
Data Science And Big Data Computing written by Zaigham Mahmood and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-05 with Business & Economics categories.
This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.
Smart Grid Using Big Data Analytics
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Author : Robert C. Qiu
language : en
Publisher: John Wiley & Sons
Release Date : 2017-01-23
Smart Grid Using Big Data Analytics written by Robert C. Qiu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-23 with Technology & Engineering categories.
This book is aimed at students in communications and signal processing who want to extend their skills in the energy area. It describes power systems and why these backgrounds are so useful to smart grid, wireless communications being very different to traditional wireline communications.
Cognitive Networked Sensing And Big Data
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Author : Robert Qiu
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-08-04
Cognitive Networked Sensing And Big Data written by Robert Qiu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-04 with Technology & Engineering categories.
Wireless Distributed Computing and Cognitive Sensing defines high-dimensional data processing in the context of wireless distributed computing and cognitive sensing. This book presents the challenges that are unique to this area such as synchronization caused by the high mobility of the nodes. The author will discuss the integration of software defined radio implementation and testbed development. The book will also bridge new research results and contextual reviews. Also the author provides an examination of large cognitive radio network; hardware testbed; distributed sensing; and distributed computing.
Mathematics Of Big Data
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Author : Jeremy Kepner
language : en
Publisher: MIT Press
Release Date : 2018-07-17
Mathematics Of Big Data written by Jeremy Kepner and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-17 with Computers categories.
The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies. Today, the volume, velocity, and variety of data are increasing rapidly across a range of fields, including Internet search, healthcare, finance, social media, wireless devices, and cybersecurity. Indeed, these data are growing at a rate beyond our capacity to analyze them. The tools—including spreadsheets, databases, matrices, and graphs—developed to address this challenge all reflect the need to store and operate on data as whole sets rather than as individual elements. This book presents the common mathematical foundations of these data sets that apply across many applications and technologies. Associative arrays unify and simplify data, allowing readers to look past the differences among the various tools and leverage their mathematical similarities in order to solve the hardest big data challenges. The book first introduces the concept of the associative array in practical terms, presents the associative array manipulation system D4M (Dynamic Distributed Dimensional Data Model), and describes the application of associative arrays to graph analysis and machine learning. It provides a mathematically rigorous definition of associative arrays and describes the properties of associative arrays that arise from this definition. Finally, the book shows how concepts of linearity can be extended to encompass associative arrays. Mathematics of Big Data can be used as a textbook or reference by engineers, scientists, mathematicians, computer scientists, and software engineers who analyze big data.
Handbook Of Big Data
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Author : Peter Bühlmann
language : en
Publisher: CRC Press
Release Date : 2016-02-22
Handbook Of Big Data written by Peter Bühlmann and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-22 with Business & Economics categories.
Handbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science, this handbook presents a carefully curated collection of techniques from both industry and academia. Thus, the text instills a working understanding of key statistical
Foundations Of Computational Finance With Matlab
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Author : Ed McCarthy
language : en
Publisher: John Wiley & Sons
Release Date : 2018-05-29
Foundations Of Computational Finance With Matlab written by Ed McCarthy and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-29 with Business & Economics categories.
Graduate from Excel to MATLAB® to keep up with the evolution of finance data Foundations of Computational Finance with MATLAB® is an introductory text for both finance professionals looking to branch out from the spreadsheet, and for programmers who wish to learn more about finance. As financial data grows in volume and complexity, its very nature has changed to the extent that traditional financial calculators and spreadsheet programs are simply no longer enough. Today’s analysts need more powerful data solutions with more customization and visualization capabilities, and MATLAB provides all of this and more in an easy-to-learn skillset. This book walks you through the basics, and then shows you how to stretch your new skills to create customized solutions. Part I demonstrates MATLAB’s capabilities as they apply to traditional finance concepts, and PART II shows you how to create interactive and reusable code, link with external data sources, communicate graphically, and more. Master MATLAB’s basic operations including matrices, arrays, and flexible data structures Learn how to build your own customized solutions when the built-ins just won’t do Learn how to handle financial data and industry-specific variables including risk and uncertainty Adopt more accurate modeling practices for portfolios, options, time series, and more MATLAB is an integrated development environment that includes everything you need in one well-designed user interface. Available Toolboxes provide tested algorithms that save you hours of code, and the skills you learn using MATLAB make it easier to learn additional languages if you choose to do so. Financial firms are catching up to universities in MATLAB usage, so this is skill set that will follow you throughout your career. When you’re ready to step into the new age of finance, Foundations of Computational Finance with MATLAB provides the expert instruction you need to get started quickly.