数据科学的多媒体

Shu‐Ching Chen
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引用次数: 0

摘要

在当今的数字世界中,随着数据的指数级增长,聚合和分析数据的新方法为许多领域带来了可观的收益,例如医疗保健、物联网、社交媒体、商业和公共政策。数据科学(DS)被认为是一个跨学科领域,涵盖了如何准备、分析、解释、建模和呈现数据。它结合了数据分析、机器学习、数学和统计学,以及领域和商业知识。DS的主要目标之一是利用大数据技术和熟练的分析,从数据中获取尽可能多的信息,促进决策过程。许多研究领域,如医学和天体物理学都大量使用了DS,通常侧重于结构化的科学数据。使用DS,科学家可以更好地理解数据并进行更精确的分析。此外,基于机器学习和领域知识的正确组合,DS已经成为人工智能的重要基础,并通过发现数据中的新知识和隐藏意义,继续影响生活的各个方面。
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Multimedia for Data Science
In today's digital world, with the exponential growth of data, new approaches to aggregate and analyze data are bringing considerable benefits to many fields, such as healthcare, Internet of Things, social media, business, and public policy. Data science (DS) is considered as an interdisciplinary field that covers how data is prepared, analyzed, interpreted, modeled, and presented. It is a combination of data analytics, machine learning, math, and statistics, as well as domain and business knowledge. One of the main goals of DS is to leverage Big Data technologies with an adept analysis to obtain as much information as possible from the data and facilitate the decision-making process. Many research areas such as medicine and astrophysics have heavily utilized DS, usually focusing on structured scientific data. Using DS, the scientist can obtain a better understanding of the data and conduct a more precise analysis. In addition, DS has become a crucial foundation for artificial intelligence based on the right mix of machine learning and domain knowledge and continued to impact all aspects of life, through the discovery of new knowledge and hidden meaning within the data.
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