Data science for business: [what you need to know about data mining and data-analytic thinking]
(Book)
Author:
Contributors:
Published:
Sebastopol, Calif. : O'Reilly, 2013.
Format:
Book
Edition:
1st ed.
Physical Desc:
xxi, 386 pages : illustrations ; 24 cm
Status:
ASU Main (3rd floor)
QA76.9.D343 P76 2013
Copies
Location
Call Number
Status
Last Check-In
ASU Main (3rd floor)
QA76.9.D343 P76 2013
On Shelf
May 13, 2024
Citations
APA Citation (style guide)
Provost, F., & Fawcett, T. (2013). Data science for business: [what you need to know about data mining and data-analytic thinking]. Sebastopol, Calif., O'Reilly.
Chicago / Turabian - Author Date Citation (style guide)Provost, Foster, 1964- and Tom. Fawcett. 2013. Data Science for Business: [what You Need to Know About Data Mining and Data-analytic Thinking]. Sebastopol, Calif., O'Reilly.
Chicago / Turabian - Humanities Citation (style guide)Provost, Foster, 1964- and Tom. Fawcett, Data Science for Business: [what You Need to Know About Data Mining and Data-analytic Thinking]. Sebastopol, Calif., O'Reilly, 2013.
MLA Citation (style guide)Provost, Foster and Tom Fawcett. Data Science for Business: [what You Need to Know About Data Mining and Data-analytic Thinking]. Sebastopol, Calif., O'Reilly, 2013.
Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
Description
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.
More Details
Language:
English
ISBN:
1449361323, 9781449361327
Notes
General Note
Subtitle from cover.
Bibliography
Includes bibliographical references (pages 361-368) and index.
Description
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.
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Grouped Work ID:
a0a953c9-6c6d-e928-3e58-d98cd60dce82
Record Information
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| 100 | 1 | |a Provost, Foster, |d 1964- |0 https://id.loc.gov/authorities/names/n00016761 | |
| 245 | 1 | 0 | |a Data science for business : |b [what you need to know about data mining and data-analytic thinking] / |c Foster Provost and Tom Fawcett. |
| 246 | 1 | 4 | |a What you need to know about data mining and data-analytic thinking |
| 250 | |a 1st ed. | ||
| 264 | 1 | |a Sebastopol, Calif. : |b O'Reilly, |c 2013. | |
| 300 | |a xxi, 386 pages : |b illustrations ; |c 24 cm | ||
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| 500 | |a Subtitle from cover. | ||
| 504 | |a Includes bibliographical references (pages 361-368) and index. | ||
| 505 | 0 | |a 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 | |a 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 | |a Data mining. |0 https://id.loc.gov/authorities/subjects/sh97002073 | |
| 650 | 0 | |a Big data. |0 https://id.loc.gov/authorities/subjects/sh2012003227 | |
| 650 | 0 | |a Information science. |0 https://id.loc.gov/authorities/subjects/sh85066150 | |
| 650 | 0 | |a Business |x Data processing. |0 https://id.loc.gov/authorities/subjects/sh85018264 | |
| 650 | 7 | |a Sciences de l'information. |2 eclas | |
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| 650 | 4 | |a Sciences de l'information. | |
| 650 | 2 | |a Data Mining. |0 https://id.nlm.nih.gov/mesh/D057225 | |
| 650 | 2 | |a Information Science. |0 https://id.nlm.nih.gov/mesh/D007254 | |
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| 700 | 1 | |a Fawcett, Tom. |0 https://id.loc.gov/authorities/names/n2004016206 | |
| 856 | 4 | 2 | |z Additional Information at Google Books |u http://books.google.com/books?isbn=1449361323 |
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