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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 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. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. Bestandsnummer des Verkäufers GOR009840019
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.
Über die Autorin bzw. den Autor: John D. Kelleher is Academic Leader of the Information, Communication, and Entertainment Research Institute at Technological University Dublin. He is the coauthor of Data Science and the author of Deep Learning, both in the MIT Press Essential Knowledge series.
Titel: Data Science (The MIT Press Essential ...
Verlag: MIT Press Ltd, United States
Erscheinungsdatum: 2018
Einband: Paperback
Zustand: Very Good
Anbieter: Books From California, Simi Valley, CA, USA
Paperback. Zustand: Very Good. Artikel-Nr. mon0003767991
Anzahl: 10 verfügbar
Anbieter: World of Books (was SecondSale), Montgomery, IL, USA
Zustand: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. Artikel-Nr. 00103689186
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Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Artikel-Nr. G0262535432I3N00
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Anbieter: ThriftBooks-Atlanta, AUSTELL, GA, USA
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Anbieter: ThriftBooks-Reno, Reno, NV, USA
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Anbieter: ThriftBooks-Dallas, Dallas, TX, USA
Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Artikel-Nr. G0262535432I3N00
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