The essays in this co-written book examine architectural dereliction and its experience, interpretation and even appropriation in classical arts and popular culture, with a special focus on how the various forms of aestheticisation of the past can serve the understanding of our contemporary state of culture.

Transporting readers from derelict homesteads to imperiled harbors, postindustrial ruins to Cold War test sites, Curated Decay presents an unparalleled provocation to conventional thinking on the conservation of cultural heritage. Caitlin DeSilvey proposes rethinking the care of certain vulnerable sites in terms of ecology and entropy, and explains how we must adopt an ethical stance that allows us to collaborate with—rather than defend against—natural processes. Curated Decay chronicles DeSilvey’s travels to places where experiments in curated ruination and creative collapse are under way, or under consideration. It uses case studies from the United States, Europe, and elsewhere to explore how objects and structures produce meaning not only in their preservation and persistence, but also in their decay and disintegration. Through accessible and engaging discussion of specific places and their stories, it traces how cultural memory is generated in encounters with ephemeral artifacts and architectures. An interdisciplinary reframing of the concept of the ruin that combines historical and philosophical depth with attentive storytelling, Curated Decay represents the first attempt to apply new theories of materiality and ecology to the concerns of critical heritage studies.

Covering 800 years of intellectual and literary history, Prica considers the textual forms of ruins. Western ruins have long been understood as objects riddled with temporal contradictions, whether they appear in baroque poetry and drama, Romanticism’s nostalgic view of history, eighteenth-century paintings of classical subjects, or even recent photographic histories of the ruins of postindustrial Detroit. Decay and Afterlife pivots away from our immediate, visual fascination with ruins, focusing instead on the textuality of ruins in works about disintegration and survival. Combining an impressive array of literary, philosophical, and historiographical works both canonical and neglected, and encompassing Latin, Italian, French, German, and English sources, Aleksandra Prica addresses ruins as textual forms, examining them in their extraordinary geographical and temporal breadth, highlighting their variability and reflexivity, and uncovering new lines of aesthetic and intellectual affinity. Through close readings, she traverses eight hundred years of intellectual and literary history, from Seneca and Petrarch to Hegel, Goethe, and Georg Simmel. She tracks European discourses on ruins as they metamorphose over time, identifying surprising resemblances and resonances, ignored contrasts and tensions, as well as the shared apprehensions and ideas that come to light in the excavation of these discourses.

"In 'The Ruins Lesson,' the National Book Critics Circle Award-winning poet-critic Susan Stewart explores the West's fascination with ruins in literature, visual art, and architecture, covering a vast chronological and geographical range from the ancient Egyptians to T. S. Eliot. In the multiplication of images of ruins, artists, and writers she surveys, Stewart shows how these thinkers struggled to recover lessons out of the fragility or our cultural remains. She tries to understand the appeal in the West of ruins and ruination, particularly Roman ruins, in the work and thought of Goethe, Piranesi, Blake, and Wordsworth, whom she returns to throughout the book. Her sweeping, deeply felt study encompasses the founding legends of broken covenants and original sin; Christian transformations of the classical past; the myths and rituals of human fertility; images of ruins in Renaissance allegory, eighteenth-century melancholy, and nineteenth-century cataloguing; and new gardens that eventually emerged from ancient sites of disaster"--

In eleven sharp essays, the contributors to Decay attend to the processes and experiences of symbolic and material decay in a variety of sociopolitical contexts across the globe. They examine decay in its myriad manifestations—biological, physical, organizational, moral, political, personal, and social and in numerous contexts, including colonialism and imperialism, governments and the state, racism, the environment, and infrastructure. The volume's topics are wide in scope, ranging from the discourse of social decay in contemporary Australian settler colonialism and the ways infrastructures both create and experience decay to cultural decay in the aftermath of the Sri Lankan civil war and the relations among individual, institutional, and societal decay in an American high-security prison. By using decay as a problematic and expounding its mechanisms, conditions, and temporalities, the contributors provide nuanced and rigorous means to more fully grapple with the exigencies of the current sociopolitical moment. Contributors. Cameo Dalley, Peter D. Dwyer, Akhil Gupta, Ghassan Hage, Michael Herzfeld, Elise Klein, Bart Klem, Tamara Kohn, Michael Main, Fabio Mattioli, Debra McDougall, Monica Minnegal, Violeta Schubert

Deep learning neural networks have become easy to define and fit, but are still hard to configure. Discover exactly how to improve the performance of deep learning neural network models on your predictive modeling projects. With clear explanations, standard Python libraries, and step-by-step tutorial lessons, you’ll discover how to better train your models, reduce overfitting, and make more accurate predictions.

This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.

Julia Solis's photographs of abandoned theaters from across the United States and Europe conjure the remaining magic of the decaying buildings and rooms, though the screenings and performances ceased long ago -- Back cover.

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

This text provides a very simple, initial introduction to the complete scientific computing pipeline: models, discretization, algorithms, programming, verification, and visualization. The pedagogical strategy is to use one case study – an ordinary differential equation describing exponential decay processes – to illustrate fundamental concepts in mathematics and computer science. The book is easy to read and only requires a command of one-variable calculus and some very basic knowledge about computer programming. Contrary to similar texts on numerical methods and programming, this text has a much stronger focus on implementation and teaches testing and software engineering in particular.