Topic: Scientific

A creative and comprehensive exploration of the institutional forces undermining the management of environments critical to public health. For almost two decades, the citizens of western Mexico have called for...

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged...

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged...

This is the activities workbook for Active Calculus chapters 1-4. It includes only the activities from the full textbook and offers lots of place to write with each activity starting...

An innovative historical analysis of the intersection of religion and technology in making the modern state, focusing on bodily production and reproduction across the human-animal divide. In Milk and Honey, Tamar...

An intimate account of rural New England families living on the edge of homelessness, as well as the practices and policies of care that fail them. Families on the Edge is...

This text is intended as a treatise for a rigorous course introducing the elements of integration theory on the real line. All of the important features of the Riemann integral,...

An elementary introduction to integration theory on the real line. This is at the level of an honor's course in calculus or a first undergraduate level real analysis course. In...

This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data. In the new world of pervasive,...

Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective.What distinguishes reinforcement learning from...

The mathematical theory of machine learning not only explains the current algorithms but can also motivate principled approaches for the future. This self-contained textbook introduces students and researchers of AI...

This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical physics, Roberts and Yaida provide clear and pedagogical explanations...