Описание: An account of all the new and surprising evidence now available for the beginnings of the earliest civilizations that contradict the standard narrative
Описание: Title: Declaration and testimony, for the doctrine and order of the church of Christ, and against the errors of the present times: to which is prefixed, A narrative concerning the maintainance of the Reformation-testimony.
Author: Associate Presbytery of Pennsylvania (1782-1801)
Publisher: Gale, Sabin Americana
Description:
Based on Joseph Sabin's famed bibliography, Bibliotheca Americana, Sabin Americana, 1500--1926 contains a collection of books, pamphlets, serials and other works about the Americas, from the time of their discovery to the early 1900s. Sabin Americana is rich in original accounts of discovery and exploration, pioneering and westward expansion, the U.S. Civil War and other military actions, Native Americans, slavery and abolition, religious history and more.
Sabin Americana offers an up-close perspective on life in the western hemisphere, encompassing the arrival of the Europeans on the shores of North America in the late 15th century to the first decades of the 20th century. Covering a span of over 400 years in North, Central and South America as well as the Caribbean, this collection highlights the society, politics, religious beliefs, culture, contemporary opinions and momentous events of the time. It provides access to documents from an assortment of genres, sermons, political tracts, newspapers, books, pamphlets, maps, legislation, literature and more.
Now for the first time, these high-quality digital scans of original works are available via print-on-demand, making them readily accessible to libraries, students, independent scholars, and readers of all ages.
++++ The below data was compiled from various identification fields in the bibliographic record of this title. This data is provided as an additional tool in helping to insure edition identification: ++++
SourceLibrary: Huntington Library
DocumentID: SABCP01212200
CollectionID: CTRG94-B27
PublicationDate: 17840101
SourceBibCitation: Selected Americana from Sabin's Dictionary of books relating to America
Despite being immensely popular--and immensely lucrative--education is grossly overrated. In this explosive book, Bryan Caplan argues that the primary function of education is not to enhance students' skill but to certify their intelligence, work ethic, and conformity--in other words, to signal the qualities of a good employee. Learn why students hunt for easy As and casually forget most of what they learn after the final exam, why decades of growing access to education have not resulted in better jobs for the average worker but instead in runaway credential inflation, how employers reward workers for costly schooling they rarely if ever use, and why cutting education spending is the best remedy.
Caplan draws on the latest social science to show how the labor market values grades over knowledge, and why the more education your rivals have, the more you need to impress employers. He explains why graduation is our society's top conformity signal, and why even the most useless degrees can certify employability. He advocates two major policy responses. The first is educational austerity. Government needs to sharply cut education funding to curb this wasteful rat race. The second is more vocational education, because practical skills are more socially valuable than teaching students how to outshine their peers.
Romantic notions about education being "good for the soul" must yield to careful research and common sense--The Case against Education points the way.
A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.
Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.
After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.
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