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21277831
MIT Press Essential Knowledge Data Science, (Paperback)
Item #:
21277831
ALL 2827
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What Stands Out
Comprehensive Overview
Covers foundational concepts and applications in data science, making it suitable for beginners and experts alike, ensuring a well-rounded understanding of the field.
Accessible Format
Presented in paperback, this edition is easy to read and handle, perfectly suited for students and professionals seeking a practical guide without the burden of heavy textbooks.
Expert Insights
Authored by leading academics, this book offers authoritative perspectives and current trends in data science, providing readers with valuable insights to drive their learning and application.
Product Details
- 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.
| Publication date | April, 2018 |
| Author | MIT Press |
| Book format | Paperback |
| Genre | Computing & Internet |
| Pages | 280 |
| Age group | Adult |
| Binding type | Perfect Binding |
| Series title | MIT Press Essential Knowledge |
| Fiction/nonfiction | Non-Fiction |
| Publisher | MIT Press |
| Reading level | General, 18 |
| Subgenre | Data Science |
| Original languages | English |
| Is collectible | N |
| Bisac subject heading | Computers |
| Edition | 1 |
| Language | English |
| Pub date | 2018-04-13 |
| Item Weight | 1 lbs (450 grams) |
Who Should Buy?
-
Beginners in Data Science
Ideal for individuals new to data science, providing foundational knowledge and a clear understanding of the field.
-
Academics and Researchers
Useful for those in academia who need a concise overview of key data science concepts and methodologies.
-
Professionals Seeking Skills
Great for professionals looking to enhance their data science skills for career advancement or transition into the field.
-
Advanced Practitioners
Not suitable for individuals with extensive experience in data science; lacks advanced topics or complex theories.
Product Description
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