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Zusammenfassung: Audiovisual testimony of a witness to World War II, who rescued those targeted for Nazi persecution and/or who was involved with the planning and implementation of aid programs during and after the war. Includes pre-war, wartime, and post-war experience
Zusammenfassung: Audiovisual testimony of a Holocaust survivor. Includes pre-war, wartime, and post-war experiences
Zusammenfassung: Audiovisual testimony of a Holocaust survivor. Includes pre-war, wartime, and post-war experiences
Zusammenfassung: Audiovisual testimony of a Holocaust survivor. Includes pre-war, wartime, and post-war experiences
Learn how to build machine translation systems with deep learning from the ground up, from basic concepts to cutting-edge research.
Many applications within natural language processing involve performing text-to-text transformations, i.e., given a text in natural language as input, systems are required to produce a version of this text (e.g., a translation), also in natural language, as output. Automatically evaluating the output of such systems is an important component in developing text-to-text applications. Two approaches have been proposed for this problem: (i) to compare the system outputs against one or more reference outputs using string matching-based evaluation metrics and (ii) to build models based on human feedback to predict the quality of system outputs without reference texts. Despite their popularity, reference-based evaluation metrics are faced with the challenge that multiple good (and bad) quality outputs can be produced by text-to-text approaches for the same input. This variation is very hard to capture, even with multiple reference texts. In addition, reference-based metrics cannot be used in production (e.g., online machine translation systems), when systems are expected to produce outputs for any unseen input. In this book, we focus on the second set of metrics, so-called Quality Estimation (QE) metrics, where the goal is to provide an estimate on how good or reliable the texts produced by an application are without access to gold-standard outputs. QE enables different types of evaluation that can target different types of users and applications. Machine learning techniques are used to build QE models with various types of quality labels and explicit features or learnt representations, which can then predict the quality of unseen system outputs. This book describes the topic of QE for text-to-text applications, covering quality labels, features, algorithms, evaluation, uses, and state-of-the-art approaches. It focuses on machine translation as application, since this represents most of the QE work done to date. It also briefly describes QE for several other applications, including text simplification, text summarization, grammatical error correction, and natural language generation.
This open access volume provides insight into how organizations change through the adoption of digital technologies. Opportunities and challenges for individuals as well as the organization are addressed. It features four major themes: 1. Current research exploring the theoretical underpinnings of digital transformation of organizations. 2. Insights into available digital technologies as well as organizational requirements for technology adoption. 3. Issues and challenges for designing and implementing digital transformation in learning organizations. 4. Case studies, empirical research findings, and examples from organizations which successfully adopted digital workplace learning.
"This is the colorful and dramatic biography of two of America's most controversial entrepreneurs: Moses Louis Annenberg, 'the racing wire king, ' who built his fortune in racketeering, invested it in publishing, and lost much of it in the biggest tax evasion case in United States history; and his son, Walter, launcher of TV Guide and Seventeen magazines and former ambassador to Great Britain."--Jacket.
To uphold family honor and tradition, Sheetal Prasad is forced to forsake the man she loves and marry playboy millionaire Rakesh Dhanraj while the citizens of Raigun, India, watch in envy. On her wedding night, however, Sheetal quickly learns that the stranger she married is as cold as the marble floors of the Dhanraj mansion. Forced to smile at family members and cameras and pretend there's nothing wrong with her marriage, Sheetal begins to discover that the family she married into harbors secrets, lies and deceptions powerful enough to tear apart her world. With no one to rely on and no escape, Sheetal must ally with her husband in an attempt to protect her infant son from the tyranny of his family.sion.