In brisk and engaging prose, this comprehensive introductory textbook traverses the broad sweep of US history since 1945. Winds of Hope, Storms of Discord explores how Americans of all walks of life –a political leaders, businesspeople, public intellectuals, workers, students, activists, migrants, and others – struggled to define the nation’s political, economic, geopolitical, demographic, and social character. It chronicles the nation’s ceaseless ferment, from the rocky conversion to peacetime in the early aftermath of World War II; to the frightening emergence of the Cold War and repeated US military adventures abroad; to the struggles of African Americans and other minorities to claim a share of the American Dream; to the striking transformations in social attitudes catalysed by the women’s movement and struggles for gay and lesbian liberation; to the dynamic force of political, economic, and social conservatism. Carrying the story to the spring of 2022, Winds of Hope also shows how dizzying technological changes at times threatened to upend the nation’s civic and political life.

This chapter addresses the unique Christian doctrine of creation out of nothing (creatio ex nihilo), elaborating the basics of a creation theology. Negatively, it indicates positions ruled out (i.e., gnostic dualism, pantheist monism, naturalism); and positively, it emphasizes what is suggested about the God-world relationship in constructive relation to other Christian doctrines, scientific questions pertaining to evolution, and the ecological crisis.

This final chapter covers topics that build on the material discussed in the book, with the aim of pointing to avenues for further study and research. The selection of topics is clearly a matter of personal choice, but care has been taken to present both well-established topics, such as probabilistic graphical models, and emerging ones, such as causality and quantum machine learning. The topics are distinct, and each section can be read separately. The presentation is brief, and only meant as a launching pad for exploration.

This chapter examines the person and work of the Holy Spirit, the historically neglected member of the Trinity. Tracing the biblical basis and the early church’s discernment of the Spirit’s personhood and deity, it draws from the renewed appreciation of pneumatology in recent theology to situate the Spirit’s work in redemption within the larger context of the Spirit’s work in creation.

In brisk and engaging prose, this comprehensive introductory textbook traverses the broad sweep of US history since 1945. Winds of Hope, Storms of Discord explores how Americans of all walks of life –a political leaders, businesspeople, public intellectuals, workers, students, activists, migrants, and others – struggled to define the nation’s political, economic, geopolitical, demographic, and social character. It chronicles the nation’s ceaseless ferment, from the rocky conversion to peacetime in the early aftermath of World War II; to the frightening emergence of the Cold War and repeated US military adventures abroad; to the struggles of African Americans and other minorities to claim a share of the American Dream; to the striking transformations in social attitudes catalysed by the women’s movement and struggles for gay and lesbian liberation; to the dynamic force of political, economic, and social conservatism. Carrying the story to the spring of 2022, Winds of Hope also shows how dizzying technological changes at times threatened to upend the nation’s civic and political life.

As discussed so far in this book, the standard formulation of machine learning makes the following two basic assumptions: 1. Statistical equivalence of training and testing. The statistical properties of the data observed during training match those to be experienced during testing – i.e., the population distribution underlying the generation of the data is the same during both training and testing. 2. Separation of learning tasks. Training is carried out separately for each separate learning task – i.e., for any new data set and/or loss function, training is viewed as a new problem to be addressed from scratch.

In this chapter, we use the optimization tools presented in Chapter 5 to develop supervised learning algorithms that move beyond the simple settings studied in Chapter 4 for which the training problem could be solved exactly, typically by addressing an LS problem. We will focus specifically on binary and multi-class classification, with a brief discussion at the end of the chapter about the (direct) extension to regression problems. Following Chapter 4, the presentation will mostly concentrate on parametric model classes, but we will also touch upon mixture models and non-parametric methods.

Starting with Christianity’s Jewish heritage and Greco-Roman context, this chapter surveys the early theological efforts of the “apostolic fathers,” the apologists under Roman persecution, and the emergence of a fledgling “orthodoxy” through the crucial theological work of the church fathers against the backdrop of “heresy.” It then explores the canonization of the New Testament text, the development of the doctrines of the Trinity and christology, and the key contributions of Augustine in the West and the Cappadocians in the East as the apex of patristic theology.