Publisher description

More than ninety percent of all scientific history has been made during the last half century. So far, however, only a fraction of historical scholarship has dealt with this period. Merely a decade ago, most scientific historians considered recent science - the scientific culture created, lived and remembered by contemporary scientists - an area of study best left to the historical actors themselves.

Bringing together authorities on the history, historiography and methodology of recent and contemporary science, this book reviews the problems facing historians of technology, contemporary science and medicine and explores new ways forward.

As historians of science increasingly turn to work on recent (post 1945) science, the historiographical and methodological problems associated with the history of contemporary science are debated with growing frequency and urgency. Bringing together authorities on the history, historiography and methodology of recent and contemporary science, this book reviews the problems facing historians of technology, contemporary science and medicine, and explores new ways forward. With contributions from key researchers in the field, the text covers topics that will be of ever increasing interest to historians of post-war science, including the difficulties of accessing and using secret archival material, the interactions between archivists, historians and scientists, and the politics of evidence and historical accounts.

An introductory A-Z resource detailing the scientific achievements of the contemporary world and analyzing the key scientific trends, discoveries, and personalities of the modern age.

The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. 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.

Are science and technology independent of one another? Is technology dependent upon science, and if so, how is it dependent? Is science dependent upon technology, and if so how is it dependent? Or, are science and technology becoming so interdependent that the line dividing them has become totally erased? This book charts the history of technoscience from the late nineteenth century to the end of the twentieth century and shows how the military–industrial–academic complex and big science combined to create new examples of technoscience in such areas as the nuclear arms race, the space race, the digital age, and the new worlds of nanotechnology and biotechnology.