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Christianity as a Way of Life
Focusing on Christianity’s core practices, a leading theologian imagines Christianity as a way of life oriented toward wisdom A Seminary Coop Notable Book of 2023 In this book, Kevin W. Hector argues that we can understand Christianity as a set of practices designed to transform one’s way of perceiving and being in the world. Hector examines practices that reorient us to God (imitation, corporate singing, eating together, friendship, and likemindedness), that transform our way of being in the world (prayer, wonder, laughter, lament, and vocation), and that reshape our way of being with others (benevolence, looking for the image of God in others, forgiveness, and activism). Taken together...
Applied Data Science
This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science...
Probabilistic Machine Learning for Finance and Investing
Whether based on academic theories or discovered empirically by humans and machines, all financial models are at the mercy of modeling errors that can be mitigated but not eliminated. Probabilistic ML technologies are based on a simple and intuitive definition of probability and the rigorous calculus of probability theory. Unlike conventional AI systems, probabilistic machine learning (ML) systems treat errors and uncertainties as features, not bugs. They quantify uncertainty generated from inexact model inputs and outputs as probability distributions, not point estimates. Most importantly, these systems are capable of forewarning us when their inferences and predictions are no longer useful...
Probabilistic Deep Learning
Probabilistic Deep Learning is a hands-on guide to the principles that support neural networks. Learn to improve network performance with the right distribution for different data types, and discover Bayesian variants that can state their own uncertainty to increase accuracy. This book provides easy-to-apply code and uses popular frameworks to keep you focused on practical applications. Summary Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingly popular probabilistic approach to deep learning that allows you to refine your results more quickly and accurately without much trial-and-error testing. Emphasizing practical techniques that use the Pyt...
Artificial Neural Networks in Pattern Recognition
This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.
The Future of the United Nations System
What does the future hold for the UN? In this book, twenty-two scholars from all continents contribute twelve chapters that cover prevention of violence, creating economic and social structures that sustain human fulfilment, sharing and protecting the commons, and peace education. The search for future potential, based on experience in these twelve "laboratories," leads to sixty-six recommendations for new institutions and programs on issues that include controlling weapons, humanitarian intervention, collaboration between UN peacekeepers and NGOs, human rights, economic policies, advancement of women, refugees, ecological security, communications, and peace education. These recommendations ...
Entec Directory Of Environmental Technology European Edition
The Entec Directory of Environmental Technology, European Edition is the only comprehensive reference to cover producers and users of goods and services in these areas of environmental concern: Water Air Solid waste Hazardous waste Noise vibration Energy Information, including up-to-date names and addresses, is featured for more than 20,000 companies from the 20 countries of Western Europe. Thousands of products, processes, and services have been categorized under 865 specific products and service groups. Never before has such a massive reference to European environmental goods and services been compiled. The book will be invaluable to anyone in government, industry, science and education, or the professional arena who would like to utilize European environmental technology.
Der Engel Mächte
Wieso glauben Menschen an Engel? Und wie stellt sich eigentlich Theologie diesem Phanomen? Oliver Durr widmet sich diesen Fragen und zieht dabei einen roten Faden von den religionsgeschichtlichen Anfangen uber biblische und theologiegeschichtliche Befunde bis in die gegenwartige Diskussion hinein. Er verbindet damit aber auch den systematischen und methodologischen Ausblick, wie nach der Kritik an der Engellehre durch Reformation und Metaphysikkritik ein heutiges Verstandnis von Engeln, Teufel und Damonen in moderner Theologie vertreten werden kann, ohne in die Aporien alter Diskussionen zuruckzufallen. Das Buch bietet dadurch TheologInnen, PfarrerInnen und theologisch Interessierten neue systematisch-theologische Perspektiven im Umgang mit dem volkskirchlich tief verankerten Engelglauben.
Artificial Neural Networks in Pattern Recognition
This book constitutes the refereed proceedings of the 8th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2018, held in Siena, Italy, in September 2018. The 29 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest research in all areas of neural network- and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications. Chapter "Bounded Rational Decision-Making with Adaptive Neural Network Priors" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Ensemble Methods for Machine Learning
In Ensemble Methods for Machine Learning you'll learn to implement the most important ensemble machine learning methods from scratch. Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real-world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
