Discover Digital Libraries: Theory And Practice Mobi Download Bookl

0 views

Skip to first unread message

Message has been deleted

Calvin Beauchamps

unread,

Jul 12, 2024, 6:11:26 PM7/12/24

to gapharrisynth

This book is intended for researchers, designers, librarians, archivists, teachers, and graduate students who are interested in digitization, digital library development, management, use, and evaluation. The comprehensive literature review on theory and practice of digital libraries will provide a foundation for education, research, and practice. The implication discussion offers guidance for designers and librarians in designing and evaluating digital libraries for the general public, as well as for specific user groups. This book can also serve as a textbook for digital library education in library and information science programs as well as affiliated programs.

A dramatic increase in computing power has enabled new areas of data science to develop in statistical modeling and analysis. These areas cover predictive and descriptive learning bridge ideas and theory in statistics, computer science and artificial intelligence. We will cover many of these new methods including predictive learning such as estimating models from data to predict future outcomes, notably regression and classification models. Regression topics include linear regression with recent advances to deal with large numbers of variables, smoothing techniques, additive models, and local regression. Classification topics include discriminant analysis, logistic regression, support vector machines, generalized additive models, naive Bayes, mixture models and nearest neighbor methods. Lastly we develop neural networks and deep learning techniques, bridging the theory introduced in the earlier parts of the class to purely empirical methods. We situate these methods in the "data science lifecycle" as part of the larger set of practices in the discovery and communication of scientific findings.