Data science [electronic resource] / John D. Kelleher and Brendan Tierney.
Series InformationMIT Press essential knowledge series.
- ISBN: 9781469096773 (sound recording : hoopla Audio Book)
- ISBN: 1469096773 (sound recording : hoopla Audio Book)
- Physical Description: 1 online resource (1 audio file (5hr., 51 min.)) : digital.
- Edition: Unabridged.
- Publisher: [United States] : Gildan, 2018.
- Distributor: Made available through hoopla
|Restrictions on Access Note:||
Digital content provided by hoopla.
|Participant or Performer Note:||
Read by Chris Sorensen.
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.
|System Details Note:||
Mode of access: World Wide Web.
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