008 |
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170704s2013 cau a b 001 0 eng |
020 |
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|a9781449361327 (pbk.) :|cUSD39.99
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040 |
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|aNOU|beng
|
050 |
4
|
|aQA76.9.D343|bP76 2013
|
095 |
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|aLB|bLBF|pbook|dQA76.9.D343|eP969|y2013|fcelin|cE019468|n1036
|
100 |
1
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|aProvost, Foster,|d1964-
|
245 |
10
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|aData science for business /|cFoster Provost and Tom Fawcett.
|
246 |
14
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|aData science for business :|bwhat you need to know about data mining and data-analytic thinking
|
250 |
|
|a1st ed.
|
260 |
|
|aSebastopol, CA :|bO'Reilly,|c2013.
|
300 |
|
|axxi, 386 p. :|bill. ;|c24 cm.
|
504 |
|
|aIncludes bibliographical references (p. 361-368) and index.
|
505 |
0
|
|aIntroduction : data-analytic thinking -- Business problems and data science solutions -- Introduction to predictive modeling : from correlation to supervised segmentation -- Fitting a model to data -- Overfitting and its avoidance -- Similarity, neighbors, and clusters -- Decision analytic thinking I : what is a good model? -- Visualizing model performance -- Evidence and probabilities -- Representing and mining text -- Decision analytic thinking II : toward analytical engineering -- Other data science tasks and techniques -- Data science and business strategy -- Conclusion.
|
520 |
|
|aProvides an introduction to the fundamental principles of data science, walking the reader through the "data-analytic thinking" necessary for extracting useful knowledge and business value from collected data.
|
650 |
0
|
|aData mining.
|
650 |
0
|
|aBig data.
|
650 |
0
|
|aInformation science.
|
650 |
0
|
|aBusiness|xData processing.
|
700 |
1
|
|aFawcett, Tom.
|