Bücher von Oliver Durr

Neuartige Bio- und Informationstechnologien erlauben es, die Welt radikal umzugestalten. Transhumanisten versprechen sich von technischen Innovationen eine umfassende Verbesserung des Lebens und entwerfen euphorische Zukunftsszenarien. Doch was geschieht, wenn wir so leben, als ob das transhumanistische Menschenbild stimmt? Das Buch stellt den Transhumanismus auf den Prüfstand. Es zeigt dessen Schattenseiten, innere Widersprüche und entmenschlichende Tendenzen auf und konfrontiert ihn mit den Perspektiven des christlichen Glaubens. Das Schlusskapitel stellt sich konstruktiv den Fragen: Können wir die technischen Innovationen so in unser Leben integrieren, dass sie es wirklich besser machen? Wenn ja, wie genau? Und welches Menschenbild leitet uns dabei?

Probabilistic Deep Learning shows how probabilistic deep learning models gives readers the tools to identify and account for uncertainty and potential errors in their results. Starting by applying the underlying maximum likelihood principle of curve fitting to deep learning, readers will move on to using the Python-based Tensorflow Probability framework, and set up Bayesian neural networks that can state their uncertainties. Key Features· The maximum likelihood principle that underlies deep learning applications· Probabilistic DL models that can indicate the range of possible outcomes· Bayesian deep learning that allows for the uncertainty occurring in real-world situations· Applying probabilistic principles to variational auto-encoders Aimed at a reader experienced with developing machine learning or deep learning applications. About the technology Probabilistic deep learning models are better suited to dealing with the noise and uncertainty of real world data ?a crucial factor for self-driving cars, scientific results, financial industries, and other accuracy-critical applications. Oliver Dürr is professor for data science at the University of Applied Sciences in Konstanz, Germany. Beate Sick holds a chair for applied statistics at ZHAW, and works as a researcher and lecturer at the University of Zurich, and as a lecturer at ETH Zurich. Elvis Murina is a research assistant, responsible for the extensive exercises that accompany this book. Dürr and Sick are both experts in machine learning and statistics. They have supervised numerous bachelors, masters, and PhD the seson the topic of deep learning, and planned and conducted several postgraduate and masters-level deep learning courses. All three authors have been working with deep learning methods since 2013 and have extensive experience in both teaching the topic and developing probabilistic deep learning models.