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Data science (the mit press essential knowledge series), john d. kelleher, brendan tierney

360 грн

Описание

A concise introduction to the emerging field of data science, explaining its
evolution, relation to machine learning, current uses, data infrastructure
issues, and ethical challenges. \n \nThe goal of data science is to improve
decision making through the analysis of data. Today data science determines
the ads we see online, the books and movies that are recommended to us online,
which emails are filtered into our spam folders, and even how much we pay for
health insurance. This volume in the MIT Press Essential Knowledge series
offers a concise introduction to the emerging field of data science,
explaining its evolution, current uses, data infrastructure issues, and
ethical challenges. \n \nIt has never been easier for organizations to gather,
store, and process data. Use of data science is driven by the rise of big data
and social media, the development of high-performance computing, and the
emergence of such powerful methods for data analysis and modeling as deep
learning. Data science encompasses a set of principles, problem definitions,
algorithms, and processes for extracting non-obvious and useful patterns from
large datasets. It is closely related to the fields of data mining and machine
learning, but broader in scope. This book offers a brief history of the field,
introduces fundamental data concepts, and describes the stages in a data
science project. It considers data infrastructure and the challenges posed by
integrating data from multiple sources, introduces the basics of machine
learning, and discusses how to link machine learning expertise with real-world
problems. The book also reviews ethical and legal issues, developments in data
regulation, and computational approaches to preserving privacy. Finally, it
considers the future impact of data science and offers principles for success
in data science projects.