Data Science

Data Science (The MIT Press Essential Knowledge)Data Science (The MIT Press Essential Knowledge)

By 作者: John D. Kelleher – Brendan Tierney
ISBN-10 书号: 0262535432
ISBN-13 书号: 9780262535434
Release Finelybook 出版日期: 2018-04-13
pages 页数: 280

$15.95


Book Description to Finelybook sorting

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.
The 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.
It 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.
Series Foreword
Preface
Acknowledgments
1 What Is Data Science?
2 What Are Data,and What Is a Data Set?
3A Data Science Ecosystem
4Machine Learning 101
5 Standard Data Science Tasks
6Privacy and Ethics
7 Future Trends and Principles of Success
Glossary
Further Readings
References
Index
About Author


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    这本书的链接有问题 请更新一下

    Honey 3周前 (08-29) 未知系统 谷歌浏览器 Windows 10 回复

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