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Название: Introduction to Data Science
Автор: Gaoyan Ou, Zhanxing Zhu, Bin Dong
Издательство: World Scientific Publishing
Год: 2024
Страниц: 445
Язык: английский
Формат: pdf (true)
Размер: 32.9 MB
Data Science is an emerging discipline which emphasizes the cultivation of Big Data talents with interdisciplinary ability. The book systematically introduces the basic contents of Data Science, including data preprocessing and basic methods of data analysis, handling special problems (e.g. text analysis), Deep Learning, and distributed systems. In addition to systematically introducing the basic content of Data Science from a theoretical point of view, the book also provides a large number of data analysis practice cases. Its purpose is to comprehensively introduce models and algorithms in Data Science from a technical point of view. This book systematically introduces the basic theoretical content of Data Science, including data preprocessing, basic methods of data analysis, processing of special problems (such as text analysis), Deep Learning, and distributed systems. In addition, this book provides a large number of case studies for data analysis application practice. Students can conduct practical training and interact with data on the iData-Course platform.
Автор: Gaoyan Ou, Zhanxing Zhu, Bin Dong
Издательство: World Scientific Publishing
Год: 2024
Страниц: 445
Язык: английский
Формат: pdf (true)
Размер: 32.9 MB
Data Science is an emerging discipline which emphasizes the cultivation of Big Data talents with interdisciplinary ability. The book systematically introduces the basic contents of Data Science, including data preprocessing and basic methods of data analysis, handling special problems (e.g. text analysis), Deep Learning, and distributed systems. In addition to systematically introducing the basic content of Data Science from a theoretical point of view, the book also provides a large number of data analysis practice cases. Its purpose is to comprehensively introduce models and algorithms in Data Science from a technical point of view. This book systematically introduces the basic theoretical content of Data Science, including data preprocessing, basic methods of data analysis, processing of special problems (such as text analysis), Deep Learning, and distributed systems. In addition, this book provides a large number of case studies for data analysis application practice. Students can conduct practical training and interact with data on the iData-Course platform.