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Data Science - The MIT Press Essential Knowledge Series
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Data science demystified: principles, challenges, ethical considerations.
You're probably curious about data science—it's shaping our digital landscape, peeking into our online habits to inform the ads and recommendations we encounter daily. This book will demystify the buzz, leading you through the discipline's origins, its relationship with machine learning, and the real-world implications of data analysis. If ethical issues or privacy concerns cross your mind when you hear "big data," this concise guide confronts these challenges directly, ensuring you're informed about the field's complexities and its future trajectories.
Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.
Data Science - The MIT Press Essential Knowledge Series
Regular price
Compare to estimated retail price: S$24.71
- Unit price
- / per
The item you've got your eye on is secondhand. You probably already know that, but just in case!
The estimated retail price shown next to any listed item represents the first-hand prices we've seen elsewhere, or the estimated original retail price of a comparable item of the same quality, construction and material offered elsewhere in new condition.
ISBN: 9780262535434
Publisher: The MIT Press
Date of Publication: 2018-04-13
Format: Paperback
Goodreads rating: 3.91
(rated by 806 readers)
Description
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
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Data science demystified: principles, challenges, ethical considerations.
You're probably curious about data science—it's shaping our digital landscape, peeking into our online habits to inform the ads and recommendations we encounter daily. This book will demystify the buzz, leading you through the discipline's origins, its relationship with machine learning, and the real-world implications of data analysis. If ethical issues or privacy concerns cross your mind when you hear "big data," this concise guide confronts these challenges directly, ensuring you're informed about the field's complexities and its future trajectories.
Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.
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