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大数据Big_Data_Data_Mining_and_Data_Science_-_George_Dimitoglou.pdf
Big Data, Data Mining and Data Science: Algorithms, Infrastructures, Management and Security (Intelligent Computing, 2)
by George Dimitoglou
大数据、数据挖掘和数据科学：算法、基础设施、管理和安全（智能计算，2）
作者：George Dimitoglou
通过应用大数据、数据挖掘和数据科学等前沿技术，可以从海量数据集中提取洞察力。这些方法对于实现明智决策和推动许多领域、行业和领域的变革性进步至关重要。本书概述了最新的工具、方法和途径，同时还通过各种应用和案例研究强调了它们的实际用途。在数据丰富的世界中，从计算的角度来看，大数据、数据挖掘和数据科学共同利用数据来挖掘隐藏的知识并解决复杂的问题。大数据处理的是海量、高速、多样的结构化和非结构化数据。数据挖掘侧重于从大型数据集中提取有意义的模式和见解，用于预测建模和决策支持。数据科学旨在利用各种技术提取可行的见解，以解决复杂问题并推动决策。这些技术适用于各种问题和领域，如金融行业、医疗保健、电子商务和网络安全。Through the application of cutting-edge techniques like Big Data, Data Mining, and Data Science, it is possible to extract insights from massive datasets. These methodologies are crucial in enabling informed decision-making and driving transformative advancements across many fields, industries, and domains. This book offers an overview of latest tools, methods and approaches while also highlighting their practical use through various applications and case studies. From a computing perspective in our data-rich world, Big Data, Data Mining, and Data Science collectively leverage data to uncover hidden knowledge and solve complex problems. Big Data deals with the vast volumes, velocity, and variety of structured and unstructured data. Data Mining focuses on extracting meaningful patterns and insights from large datasets for predictive modeling and decision support. Data Science aims to extract actionable insights using various techniques to solve complex problems and drive decision-making. These techniques are applied to diverse problems and domains, such as the financial sector, healthcare, e-commerce, and cybersecurity.
