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Data Science (The MIT Press Essential Knowledge series),Used
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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 highperformance 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 nonobvious 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 realworld 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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- Q: What is the main focus of the book 'Data Science' by John D. Kelleher? A: The book provides a concise introduction to data science, covering its evolution, relationship to machine learning, current applications, data infrastructure issues, and ethical challenges.
- Q: How many pages does the book contain? A: The book contains 280 pages.
- Q: Who is the author of the book 'Data Science'? A: The author of the book is John D. Kelleher.
- Q: What type of binding does the book have? A: The book is available in paperback binding.
- Q: When was 'Data Science' published? A: The book was published on April 13, 2018.
- Q: What topics are covered in this book about data science? A: The book covers topics such as fundamental data concepts, stages in a data science project, data infrastructure challenges, machine learning basics, and ethical and legal issues in data science.
- Q: Is this book suitable for beginners in data science? A: Yes, the book serves as a concise introduction, making it suitable for beginners who are new to the field of data science.
- Q: Does the book discuss the ethical implications of data science? A: Yes, the book reviews ethical challenges, legal issues, and developments in data regulation related to data science.
- Q: What is the edition of the book? A: The book is published in an illustrated edition.
- Q: How does data science relate to machine learning according to the book? A: The book explains that data science is closely related to machine learning but is broader in scope, encompassing principles, algorithms, and processes for analyzing large datasets.