My Library

LEADER 00000cam a2200337 a 4500 
001    u44038 
003    SIRSI 
008    170924s2013    xxua     b    001 0 eng d 
020    1449361323 
020    9781449361327 
050 04 QA76.9.D343 |bP76 2013 
100 1  Provost, Foster,|d1964- 
245 10 Data science for business :|bwhat you need to know about 
       data mining and data-analytic thinking / |cFoster Provost 
       and Tom Fawcett. 
246 14 What you need to know about data mining and data-analytic 
       thinking 
260    Sebastopol, Calif. :|bO'Reilly,|c2013 
300    xxi,386 p:|bill ;|c24 cm. 
504    Includes bibliographical references (pages 361-368) and  
       index. 
505    Introduction : 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    Provides 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 Data mining 
650  0 Big data 
650  0 Information science 
650  0 Business|xData processing 
700 1  Fawcett, Tom