Data Science
eBook - ePub

Data Science

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

About this book

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.

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Yes, you can access Data Science by John D. Kelleher,Brendan Tierney in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Series page
  3. Title page
  4. Copyright page
  5. Table of Contents
  6. Series Foreword
  7. Preface
  8. Acknowledgments
  9. 1 What Is Data Science?
  10. 2 What Are Data, and What Is a Data Set?
  11. 3 A Data Science Ecosystem
  12. 4 Machine Learning 101
  13. 5 Standard Data Science Tasks
  14. 6 Privacy and Ethics
  15. 7 Future Trends and Principles of Success
  16. Glossary
  17. Further Readings
  18. References
  19. Index
  20. About Author