000 | 03842cam a2200493Ki 4500 | ||
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001 | 9781003111290 | ||
003 | FlBoTFG | ||
005 | 20220711212801.0 | ||
006 | m o d | ||
007 | cr cnu---unuuu | ||
008 | 211007s2021 xx ob 0|1 0 eng d | ||
040 |
_aOCoLC-P _beng _erda _epn _cOCoLC-P |
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020 |
_a9781003111290 _q(electronic bk.) |
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020 |
_a1003111297 _q(electronic bk.) |
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020 |
_a9781000423198 _q(electronic bk. : PDF) |
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020 |
_a1000423190 _q(electronic bk. : PDF) |
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020 |
_a9781000423228 _q(electronic bk. : EPUB) |
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020 |
_a1000423220 _q(electronic bk. : EPUB) |
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020 | _z0367628821 | ||
020 | _z9780367628826 | ||
024 | 7 |
_a10.1201/9781003111290 _2doi |
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035 | _a(OCoLC)1273731576 | ||
035 | _a(OCoLC-P)1273731576 | ||
050 | 4 | _aQA76.9.B45 | |
072 | 7 |
_aCOM _x021030 _2bisacsh |
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072 | 7 |
_aCOM _x021000 _2bisacsh |
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072 | 7 |
_aUN _2bicssc |
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082 | 0 | 4 |
_a005.7 _223 |
245 | 0 | 0 |
_aDATA SCIENCE AND DATA ANALYTICS : _bopportunities and challenges. |
264 | 1 |
_a[Place of publication not identified] : _bCHAPMAN & HALL CRC, _c2021. |
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300 |
_a1 online resource (1 volume) : _billustrations (black and white). |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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520 | _aData 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. | ||
588 | _aOCLC-licensed vendor bibliographic record. | ||
650 | 0 |
_aBig data. _94174 |
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650 | 7 |
_aCOMPUTERS / Database Management / Data Mining _2bisacsh _912290 |
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650 | 7 |
_aCOMPUTERS / Database Management / General _2bisacsh _910834 |
|
700 | 1 |
_aTyagi, Amit Kumar, _d1988- _eeditor. _919614 |
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856 | 4 | 0 |
_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9781003111290 |
856 | 4 | 2 |
_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf |
942 | _cEBK | ||
999 |
_c72146 _d72146 |