Data Structures and Algorithms Made Easy

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

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

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 control. Data inevitably represents the ideologies of those who control its use; data analytics and algorithms too often exclude women, the poor, and ethnic groups. In Data Action, Sarah Williams provides a guide for working with data in more ethical and responsible ways. Williams outlines a method that emphasizes collaboration among data scientists, policy experts, data designers, and the public. The approach generates policy debates, influences civic decisions, and informs design to help ensure that the voices of people represented in the data are neither marginalized nor left unheard.

The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduct

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 Loukissas argues in All Data Are Local, we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. The term data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States--Harvard's Arnold Arboretum, the Digital Public Library of America, UCLA's Television News Archive, and the real estate marketplace Zillow--Loukissas shows us how to analyze data settings rather than data sets.Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogen

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

A richly illustrated overview of the work of Neri Oxman whose design redefines computer science, digital fabrication, material science, and synthetic biology. Mediated Matter is the first comprehensive overview of Neri Oxman's groundbreaking design work. Oxman has forged a singular career across design, science, and technology over the past twenty years that includes, notably, founding the field of material ecology. Trained as both a medical doctor and an architect, she brings to design a spirit of inquiry and experimentation that includes a future-forward approach to materials--from silkworm thread to automated microrobots to a water-based fabrication platform that prints structures made from biopolymers. In her work at the MIT Media Lab, she designed products and buildings as interactive entities that are environmentally informed, biologically augmented, computationally grown, and digitally manufactured. Through richly detailed diagrams, explanatory texts, process documents, and brea

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

An illustrated guide to exploring the Universe in three dimensions.Astronomers have made remarkable discoveries about our Universe, despite their reliance on the flat projection, or 2D view, the sky has offered them. But now, drawing on the vast stores of data available from telescopes and observatories on the ground and in space, astronomers are using 3D technology to go beyond a flattened view of the cosmos. In Stars in Your Hand, Kimberly Arcand and Megan Watzke offer an illustrated guide to exploring the Universe in three dimensions, with easy-to-follow instructions for creating models of stars and constellations using a 3D printer and 3D computer imaging. Stars in Your Hand and 3D technology make learning about space an adventure. Intrigued by the stunning images from high-powered telescopes? Using this book, you can fly virtually through a 3D spacescape and hold models of cosmic objects in your hand. Arcand and Watzke outline advances in 3D technology, describe some amazing recen

Fundamental theory and practical algorithms of weakly supervised classification, emphasizing an approach based on empirical risk minimization.Standard machine learning techniques require large amounts of labeled data to work well. When we apply machine learning to problems in the physical world, however, it is extremely difficult to collect such quantities of labeled data. This book presents theory and algorithms for weakly supervised learning, a paradigm of machine learning from weakly labeled data. Emphasizing an approach based on empirical risk minimization and drawing on state-of-the-art research in weakly supervised learning, the book provides both the fundamentals of the field and the advanced mathematical theories underlying them. It can be used as a reference for practitioners and researchers and in the classroom.The book first mathematically formulates classification problems, defines common notations, and reviews various algorithms for supervised binary and multiclass classif

AI is revolutionizing the world. Here’s how democracies can come out on top.Artificial intelligence is revolutionizing the modern world. It is ubiquitous―in our homes and offices, in the present and most certainly in the future. Today, we encounter AI as our distant ancestors once encountered fire. If we manage AI well, it will become a force for good, lighting the way to many transformative inventions. If we deploy it thoughtlessly, it will advance beyond our control. If we wield it for destruction, it will fan the flames of a new kind of war, one that holds democracy in the balance. As AI policy experts Ben Buchanan and Andrew Imbrie show in The New Fire, few choices are more urgent―or more fascinating―than how we harness this technology and for what purpose. The new fire has three sparks: data, algorithms, and computing power. These components fuel viral disinformation campaigns, new hacking tools, and military weapons that once seemed like science fiction. To autocrats, AI offers

The life of trailblazing physicist Mildred Dresselhaus, who expanded our understanding of the physical world.As a girl in New York City in the 1940s, Mildred “Millie” Dresselhaus was taught that there were only three career options open to women: secretary, nurse, or teacher. But sneaking into museums, purchasing three-cent copies of National Geographic, and devouring books on the history of science ignited in Dresselhaus (1930–2017) a passion for inquiry. In Carbon Queen, science writer Maia Weinstock describes how, with curiosity and drive, Dresselhaus defied expectations and forged a career as a pioneering scientist and engineer. Dresselhaus made highly influential discoveries about the properties of carbon and other materials and helped reshape our world in countless ways―from electronics to aviation to medicine to energy. She was also a trailblazer for women in STEM and a beloved educator, mentor, and colleague. Her path wasn’t easy. Dresselhaus’s Bronx childhood was impoverishe

An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments. Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field’s proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills. After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and

How genomics reveals deep histories of inequality, going back many thousands of years. Inequality is an urgent global concern, with pundits, politicians, academics, and best-selling books all taking up its causes and consequences. In Inequality, Carles Lalueza-Fox offers an entirely new perspective on the subject, examining the genetic marks left by inequality on humans throughout history. Lalueza-Fox describes genetic studies, made possible by novel DNA sequencing technologies, that reveal layers of inequality in past societies, manifested in patterns of migration, social structures, and funerary practices. Through their DNA, ancient skeletons have much to tell us, yielding anonymous stories of inequality, bias, and suffering. Lalueza-Fox, a leader in paleogenomics, offers the deep history of inequality. He explores the ancestral shifts associated with migration and describes the gender bias unearthed in these migrations―the brutal sexual asymmetries, for example, between male Euro

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 anthology provides the first art-historical reassessment of information-based art in relation to data structures and exhibition curation. It examines such landmark e

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

State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure. Machine learning develops intelligent computer systems that are able to genera

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

Maps are widely believed to be objective, and data-rich computer-made maps are iconic examples of digital knowledge. It is often claimed that digital maps, and rational boundaries, can solve political

The world is made up of structures too small to see with the naked eye, too small tosee even with an electron microscope. Einstein established the reality of atoms and molecules in theearly 1900s. How

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,

Computational systems biology unifies the mechanistic approach of systems biologywith the data-driven approach of computational biology. Computational systems biology aims todevelop algorithms that un

The world is made up of structures too small to see with the naked eye, too small to see even with an electron microscope. Einstein established the reality of atoms and molecules in the early 1900s.

This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation. Computational finance, an excit

As this book makes clear, current use of data structures such as frames, scripts, and stereotypes in psychology, artificial intelligence, and all the other disciplines now grouped together as Cognitiv