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This book provides readers with a thorough understanding of various
research areas within the field of data science. The book
introduces readers to various techniques for data acquisition,
extraction, and cleaning, data summarizing and modeling, data
analysis and communication techniques, data science tools, deep
learning, and various data science applications. Researchers can
extract and conclude various future ideas and topics that could
result in potential publications or thesis. Furthermore, this book
contributes to Data Scientists' preparation and to enhancing their
knowledge of the field. The book provides a rich collection of
manuscripts in highly regarded data science topics, edited by
professors with long experience in the field of data science.
Introduces various techniques, methods, and algorithms adopted by
Data Science experts Provides a detailed explanation of data
science perceptions, reinforced by practical examples Presents a
road map of future trends suitable for innovative data science
research and practice
This book provides readers with a thorough understanding of various
research areas within the field of data science. The book
introduces readers to various techniques for data acquisition,
extraction, and cleaning, data summarizing and modeling, data
analysis and communication techniques, data science tools, deep
learning, and various data science applications. Researchers can
extract and conclude various future ideas and topics that could
result in potential publications or thesis. Furthermore, this book
contributes to Data Scientists' preparation and to enhancing their
knowledge of the field. The book provides a rich collection of
manuscripts in highly regarded data science topics, edited by
professors with long experience in the field of data science.
Introduces various techniques, methods, and algorithms adopted by
Data Science experts Provides a detailed explanation of data
science perceptions, reinforced by practical examples Presents a
road map of future trends suitable for innovative data science
research and practice
Kai Brussau entwickelt ein innovatives Verfahren fur die simultane
Losgrossen- und Ablaufplanung zur Optimierung von
Produktivitatssteigerungen im Produktionsprozess. Im Bereich der
Evolutionaren Algorithmen werden klassische Verfahren so
modifiziert, dass sie ohne zusatzliche manuelle Anpassung fur
unterschiedliche Problemstellungen genutzt werden konnen.
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