Data Science and Data Analytics: Opportunities and Challenges
暫譯: 數據科學與數據分析：機會與挑戰

Tyagi, Amit Kumar

Data Science and Data Analytics: Opportunities and Challenges
  • 出版商: CRC
  • 出版日期: 2021-09-23
  • 售價: $6,660
  • 貴賓價: 9.5 折 $6,327
  • 語言: 英文
  • 頁數: 464
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 0367628821
  • ISBN-13: 9780367628826
  • 相關分類: Data Science

    • 海外代購書籍(需單獨結帳)

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商品描述

Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured (labeled) and unstructured (unlabeled) data. It is the future of Artificial Intelligence (AI) and a necessity of the future to make things easier and more productive. In simple terms, data science is the discovery of data or uncovering hidden patterns (such as complex behaviors, trends, and inferences) from data. Moreover, Big Data analytics/data analytics are the analysis mechanisms used in data science by data scientists. Several tools, such as Hadoop, R, etc., are used to analyze this large amount of data to predict valuable information and for decision-making. Note that structured data can be easily analyzed by efficient (available) business intelligence tools, while most of the data (80% of data by 2020) is in an unstructured form that requires advanced analytics tools. But while analyzing this data, we face several concerns, such as complexity, scalability, privacy leaks, and trust issues.

Data science helps us to extract meaningful information or insights from unstructured or complex or large amounts of data (available or stored virtually in the cloud). Data Science and Data Analytics: Opportunities and Challenges covers all possible areas, applications with arising serious concerns, and challenges in this emerging field in detail with a comparative analysis/taxonomy.

FEATURES

  • Gives the concept of data science, tools, and algorithms that exist for many useful applications

  • Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems

  • Identifies many areas and uses of data science in the smart era

  • Applies data science to agriculture, healthcare, graph mining, education, security, etc.

Academicians, data scientists, and stockbrokers from industry/business will find this book useful for designing optimal strategies to enhance their firm's productivity.

商品描述(中文翻譯)

資料科學是一個多學科的領域，利用科學方法、過程、演算法和系統，從結構化（標記）和非結構化（未標記）數據中提取知識和見解。它是人工智慧（Artificial Intelligence, AI）的未來，也是未來使事物更簡單和更具生產力的必要條件。簡而言之，資料科學是從數據中發現或揭示隱藏模式（例如複雜行為、趨勢和推論）。此外，大數據分析（Big Data analytics）/數據分析（data analytics）是資料科學中數據科學家使用的分析機制。許多工具，如Hadoop、R等，被用來分析這大量的數據，以預測有價值的信息並進行決策。需要注意的是，結構化數據可以通過高效（可用的）商業智慧工具輕鬆分析，而大多數數據（到2020年約80%的數據）則以非結構化形式存在，這需要先進的分析工具。然而，在分析這些數據時，我們面臨著幾個問題，例如複雜性、可擴展性、隱私洩漏和信任問題。

資料科學幫助我們從非結構化、複雜或大量的數據（可用或虛擬存儲在雲端）中提取有意義的信息或見解。《資料科學與數據分析：機會與挑戰》詳細涵蓋了這個新興領域中所有可能的領域、應用及其所帶來的嚴重關注和挑戰，並進行了比較分析/分類。

特點

- 提供資料科學的概念、工具和演算法，這些工具和演算法存在於許多有用的應用中
- 提供資料科學和數據分析中的許多挑戰和機會，幫助研究人員識別研究空白或問題
- 確定資料科學在智慧時代中的許多領域和用途
- 將資料科學應用於農業、醫療保健、圖形挖掘、教育、安全等領域

學術界、數據科學家和來自產業/商業的股票經紀人將發現這本書對於設計最佳策略以提高其公司的生產力非常有用。

作者簡介

Amit Kumar Tyagi is Assistant Professor (Senior Grade), and Senior Researcher at Vellore Institute of Technology (VIT), Chennai Campus, India.

He earned his PhoD. in 2018 from Pondicherry Central University, India. He joined the Lord Krishna College of Engineering, Ghaziabad (LKCE) from 2009-2010, and 2012-2013. He was an Assistant Professor and Head - Research, Lingaya's Vidyapeeth (formerly known as Lingaya's University), Faridabad, Haryana, India in 2018-2019. His current research focuses on Machine Learning with Big data, Blockchain Technology, Data Science, Cyber Physical Systems, Smart and Secure Computing and Privacy. He has contributed to several projects such as AARIN and P3- Block to address some of the open issues related to the privacy breaches in Vehicular Applications (such as Parking) and Medical Cyber Physical Systems (MCPS). He has published more than 8 patents in the area of Deep Learning, Internet of Things, Cyber Physical Systems and Computer Vision. He was recently awarded best paper award for paper titled A Novel Feature Extractor Based on the Modified Approach of Histogram of oriented Gradient, ICCSA 2020, Italy (Europe). He is a regular member of the ACM, IEEE, MIRLabs, Ramanujan Mathematical Society, Cryptology Research Society, and Universal Scientific Education and Research Network, CSI and ISTE.

作者簡介(中文翻譯)

Amit Kumar Tyagi 是印度金奈維洛爾科技學院（VIT）助理教授（高級職級）及高級研究員。他於2018年在印度龐迪榭里中央大學獲得博士學位。他於2009-2010年及2012-2013年期間加入了加茲亞巴德的克里希納工程學院（LKCE）。在2018-2019年，他擔任哈里亞納邦法里達巴德的Lingaya's Vidyapeeth（前稱Lingaya's University）的助理教授及研究部門負責人。他目前的研究重點包括機器學習與大數據、區塊鏈技術、數據科學、網絡物理系統、智能安全計算及隱私。他參與了多個項目，如AARIN和P3-Block，以解決與車輛應用（如停車）及醫療網絡物理系統（MCPS）相關的隱私洩露問題。他在深度學習、物聯網、網絡物理系統及計算機視覺領域發表了超過8項專利。他最近因論文《基於改進的方向梯度直方圖的新型特徵提取器》在2020年意大利（歐洲）舉行的ICCSA會議中獲得最佳論文獎。他是ACM、IEEE、MIRLabs、拉馬努詹數學學會、密碼學研究學會及全球科學教育與研究網絡、CSI及ISTE的正式會員。

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