Titlebook: Weiterbildung von Ingenieuren und Naturwissenschaftlern im Kontext neuer Technologien; Eine quantitative An Anja Heine Book 2017 Springer F

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Anja Heineproblem-solving and application-oriented approach.Presents cThis book describes how companies can easily and pragmatically set up and realize the path to a data-driven enterprise, especially in the marketing practice, without external support and additional investments. Using a predictive intelligen

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Anja Heinelisieren k?nnen. Anhand des Predictive Intelligence (PI)-?kosystems werden die wichtigsten Begriffe eingeführt und erkl?rt. Das PI-Reifegradmodell beschreibt in welchen Phasen Sie ein PI-?kosystem im Unternehmen aufbauen k?nnen. Der PI-Selbsttest hilft Managern zu erkennen, von wo aus sie starten mü

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Anja Heinecrutiny of the published results. In lung nodule classification, for example, many works report results on the publicly available LIDC dataset. In theory, this should allow a direct comparison of the performance of proposed methods and assess the impact of individual contributions. When analyzing se

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Anja Heiners (e.g., related to life events) are associated with an outcome (e.g., depression). In recent years, deep learning has become a potential alternative approach for conducting such analyses by predicting an outcome from a collection of factors and identifying the most “informative” ones driving the p

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Anja Heinehave been used as a tool to analyze speech patterns and characteristics that are indicative of depression. Depression affects not only a person’s mood but also their speech patterns. Individuals with depression may exhibit changes in speech, such as slower speech rate, longer pauses, reduced pitch v

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Anja Heineg market and volatile requirements, every production process should be, if possible, optimised, reducing costs and wastes. At the same time, reconfiguration enabling flexibility through software automation and, in turn, resiliency is much pursued in the context of advanced manufacturing. One sector

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Anja Heined which saw, in the 1990s onwards, a large expansion of interest in this field. This lead to the proliferation of a number of new QSAR models, most of which involved similar methodological approaches and the use of the same data—often as specific subsets focusing on particular classes of chemicals,