Contextualizing Disaster" offers a comparative analysis of six recent highly visible disasters and several slow-burning, hidden, crises that include typhoons, tsunamis, earthquakes, chemical spills, and the unfolding consequences of rising seas and climate change. The book argues that, while disasters are increasingly represented by the media as unique, exceptional, newsworthy events, it is a m…
This exciting volume presents the work and research of the Rivers of the Anthropocene Network, an international collaborative group of scientists, social scientists, humanists, artists, policymakers, and community organizers working to produce innovative transdisciplinary research on global freshwater systems. In an attempt to bridge disciplinary divides, the essays in this volume address the c…
Developing Graphics Frameworks with Python and OpenGL shows you how to create software for rendering complete three-dimensional scenes. The authors explain the foundational theoretical concepts as well as the practical programming techniques that will enable you to create your own animated and interactive computer-generated worlds.You will learn how to combine the power of OpenGL, the most wide…
Lütkenhöner’s „Intensity Dependence of Auditory Responses“: An Instructional Example in How Not To Do Computational Neurobiology
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. 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 introduction to causal models and how to learn them from data. After explaining th…
Anomaly Detection & Behavior Prediction: Higher-Level Fusion Based on Computational Neuroscientific Principles
Think D.S.P. is an introduction to Digital Signal Processing in Python. The premise of this book (and the other books in the Think X series) is that if you know how to program, you can use that skill to learn other things. The author is writing this book because he thinks the conventional approach to digital signal processing is backward: most books (and the classes that use them) present the m…
This book is about complexity science, data structures and algorithms, intermediate programming in Python and the philosophy of science: Data structures and algorithms: A data structure is a collection that contains data elements organized in a way that supports particular operations. For example, a dictionary organizes key-value pairs in a way that provides fast mapping from keys to values, bu…
Think Bayes is an introduction to Bayesian statistics using computational methods.The premise of this book, and the other books in the Think X series, is that if you know how to program, you can use that skill to learn other topics.Most books on Bayesian statistics use mathematical notation and present ideas in terms of mathematical concepts like calculus. This book uses Python code instead of …
Squeak is a modern open-source development environment for the classic Smalltalk-80 programming language. Despite being the first purely object-oriented language and environment, Smalltalk is in many ways still far ahead of its successors in promoting a vision of an environment where everything is an object, and anything can change at run-time. Squeak by Example, intended for both students and …