Data Science
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Audible会員プラン 無料体験
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ナレーター:
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Chris Sorensen
このコンテンツについて
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.
©2018 Massachusetts Institute of Technology (P)2018 Gildan Mediaこちらもおすすめ
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- 再生時間: 10 時間 28 分
- 完全版
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総合評価
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ナレーション
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ストーリー
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ストーリー
In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art.
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