Discusses types of government, international organizations, and global politics, and explains how to create and interpret the charts, tables, and graphs used to display different types of information about global politics.

The essential characteristic of a dynamic graphical method is the direct manipulation of elements of a graph on a computer screen, which in high-performance implementations, the elements change virtually instantaneously on the screen. This book contains a collection of papers about dynamic graphics dating from the late 1960s to 1988. Although technology has advanced considerably, the fundamental ideas about basic graphical principles and data-analytic goals are still relevant today.

Discusses where crime occurs, types of crime, and how crimes are tried and punished, and explains how to create and interpret the charts, tables, and graphs used to display different types of information about crime and criminals.

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

INSTANT NEW YORK TIMES BESTSELLER A NEW YORK TIMES NOTABLE BOOK OF 2018 ONE OF THE ECONOMIST'S BOOKS OF THE YEAR "My new favorite book of all time." --Bill Gates If you think the world is coming to an end, think again: people are living longer, healthier, freer, and happier lives, and while our problems are formidable, the solutions lie in the Enlightenment ideal of using reason and science. By the author of the new book, Rationality. Is the world really falling apart? Is the ideal of progress obsolete? In this elegant assessment of the human condition in the third millennium, cognitive scientist and public intellectual Steven Pinker urges us to step back from the gory headlines and prophecies of doom, which play to our psychological biases. Instead, follow the data: In seventy-five jaw-dropping graphs, Pinker shows that life, health, prosperity, safety, peace, knowledge, and happiness are on the rise, not just in the West, but worldwide. This progress is not the result of some cosmic force. It is a gift of the Enlightenment: the conviction that reason and science can enhance human flourishing. Far from being a naïve hope, the Enlightenment, we now know, has worked. But more than ever, it needs a vigorous defense. The Enlightenment project swims against currents of human nature--tribalism, authoritarianism, demonization, magical thinking--which demagogues are all too willing to exploit. Many commentators, committed to political, religious, or romantic ideologies, fight a rearguard action against it. The result is a corrosive fatalism and a willingness to wreck the precious institutions of liberal democracy and global cooperation. With intellectual depth and literary flair, Enlightenment Now makes the case for reason, science, and humanism: the ideals we need to confront our problems and continue our progress.

Discusses where immigrants come from, reasons to move, and what life is like once they arrive, and explains how to create and interpret the charts, tables, and graphs used to display different types of information about immigration.