Data Structures Using C

A proposal that we think about digital technologies such as machine learning not in terms of artificial intelligence but as artificial communication.Algorithms that work with deep learning and big data are getting so much better at doing so many things that it makes us uncomfortable. How can a device know what our favorite songs are, or what we should write in an email? Have machines become too smart? In Artificial Communication, Elena Esposito argues that drawing this sort of analogy between algorithms and human intelligence is misleading. If machines contribute to social intelligence, it will not be because they have learned how to think like us but because we have learned how to communicate with them. Esposito proposes that we think of “smart” machines not in terms of artificial intelligence but in terms of artificial communication.To do this, we need a concept of communication that can take into account the possibility that a communication partner may be not a human being but an al

How to use data as a tool for empowerment rather than oppression. Big data can be used for good--from tracking disease to exposing human rights violations--and for bad--implementing surveillance and c

Information retrieval is the foundation for modern search engines. This textbook offers an introduction to the core topics underlying modern search tehnologies, including algorithms, data structures,

Advances in training models with log-linear structures, with topics including variable selection, the geometry of neural nets, and applications.Log-linear models play a key role in modern big data and

This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based t

Big Data is made up of lots of little data: numbers entered into cell phones,addresses entered into GPS devices, visits to websites, online purchases, ATM transactions, and anyother activity that leav

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deplo

How to analyze data settings rather than data sets, acknowledging the meaning-making power of the local.In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Lo

Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identi

We live in an interoperable world. Computer hardware and software products from different manufacturers can exchange data within local networks and around the world using the Internet. The competitio

Using bioinformatics methods to generate a systems-level view of the immune system; description of the main biological concepts and the new data-driven algorithms.Despite the fact that advanced bioinf

Drawing on nationally representative telephone surveys conducted from 1995 to 2000, James Katz and Ronald Rice offer a rich and nuanced picture of Internet use in America. Using quantitative data, as

The Structure of Typed Programming Languages describes the fundamental syntactic and semantic features of modern programming languages, carefully spelling out their impacts on language design. Using c

Developed as the text for the basic computer architecture course at MIT, Computation Structures integrates a thorough coverage of digital logic design with a comprehensive presentation of computer ar

A textbook that uses a hands-on approach to teach principles of programming languages, with Java as the implementation language.This introductory textbook teaches the principles of programming languages by using an experiential learning style, in which students learn about language features by realizing those features in a pedagogical compiler. Students use Java―the most commonly used programming language in the first two years of the computer science curriculum―as the implementation language throughout. The book also discusses a range of emerging topics in programming languages missing from existing textbooks, including concurrency, Big Data, and event-driven programming. The goal is to prepare students to design, implement, analyze, and understand both domain-specific and general-purpose programming languages. The book first develops basic concepts in languages, including means of computation using primitive values, means of combination such as variable definition and functions, an

A wake-up call for America to create a new framework for democratizing data.Public data are foundational to our democratic system. People need consistently high-quality information from trustworthy so

A guide to all aspects of experimental design and data analysis for fMRI experiments, completely revised and updated for the second edition. Functional magnetic resonance imaging (fMRI), which allows

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 rapid

Machine learning -- programming computers to learn from data -- has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transactio

"Big Data" is on the covers of Science, Nature, the Economist, andWired magazines, on the front pages of the Wall Street Journal and theNew York Times. But despite the media hyperbol

This definitive study uses theory, history, and data to analyze the evolution of the US brewing industry from a fragmented market to an emerging oligopoly. Drawing on a rich and extensive data set and

This book focuses on recent developments in representational and processing aspects of complex data-intensive applications. Until recently, information systems have been designed around different bu

Data-Parallel Programming demonstrates that architecture-independent parallel programming is possible by describing in detail how programs written in a high-level SIMD programming language may be comp

The entanglements of people and data, code and space, knowledge and power: how data and algorithms shape the world―and shape us within that world.With the emergence of a post-truth world, we have witnessed the dissolution of the common ground on which truth claims were negotiated, individual agency enacted, and public spheres shaped. What happens when, as Nietzsche claimed, there are no facts, but only interpretations? In this book, Mark Shepard examines the entanglements of people and data, code and space, knowledge and power that have produced an uncommon ground―a disaggregated public sphere where the extraction of behavioral data and their subsequent processing and sale have led to the emergence of micropublics of ever-finer granularity. Shepard explores how these new post-truth territories are propagated through machine learning systems and social networks, which shape the public and private spaces of everyday life. He traces the balkanization and proliferation of online news and t

How legacy firms can combine their traditional strengths with the power of data and digital ecosystems to forge a new competitive strategy for the digital era.How can legacy firms remain relevant in the digital era? In The Future of Competitive Strategy, strategic management expert Mohan Subramaniam explains how firms can leverage both their traditional strengths and the modern-day power of data and digital ecosystems to forge a new competitive strategy. Drawing on the experiences of a range of companies, including Caterpillar, Sleep Number, and Whirlpool, he explains how firms can benefit from data’s enlarged role in modern business, develop digital ecosystems tailored to their unique business needs, and use new frameworks to harness the power of data for competitive advantage. Subramaniam presents digital ecosystems as a combination of production and consumption ecosystems, which can be used by legacy firms to unlock the value of data at various levels―from improving operational effi

How the communist revolution failed, presented in a series of catastrophes.The communist project in the twentieth century grew out of utopian desires to oppose oppression and abolish class structures,

A book at the intersection of data science and media studies, presenting concepts and methods for computational analysis of cultural data. How can we see a billion images? What analytical methods can

An argument that children are born to assign structures to their ambient language, yielding a view of language variation not based on parameters defined at UG.In this book, David Lightfoot argues that

How digital technology is profoundly renewing our sense of what is real and how we perceive.Digital technologies are not just tools; they are structures of perception. They determine the way in which

A global guide to sewers that celebrates the magnificently designed and engineered structures beneath the world's great cities.The sewer, in all its murkiness, filthiness, and subterranean seclusion,

An investigation of the irrational and the unconventional currents swirling behind the Bauhaus's signature sleek surfaces and austere structures. The Bauhaus (1919-1933) is widely regarded as the tw

A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework.Today many information source

In Decoding the Social World, Sandra González-Bailón shows how algorithms, crowdsourcing, and digital traces offer methods and data that can help us solve the puzzle of unintended consequences -- a s

Key to understanding and addressing climate change is continuous and precise monitoring of environmental conditions. Satellites play an important role in collecting climate data, offering comprehensiv

If the twentieth century was tyrannized by images, then the twenty-first is ruled by data. In Technologies of Vision, Steve Anderson argues that visual culture and the methods developed to study it h

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk a

In 1959, the electronics manufacturer Stromberg-Carlson produced the S-C 4020, a device that allowed mainframe computers to present and preserve images. In the mainframe era, the output of text and im

The human brain is often described as the most complex object in the universe. Tens of billions of nerve cells-tiny tree-like structures -- make up a massive network with enormous computational power.

Our awareness of time and temporal properties is a constant feature of consciouslife. Subjective temporality structures and guides every aspect of behavior and cognition,distinguishing memory, percept

Thanks to advances in molecular science and microscopy, we can visualize matter on ananoscale, and structures not visible to the naked eye can be visualized and characterized. The factthat technology