| Description |
xxi,386 p: ill ; 24 cm. |
| Bibliography |
Includes bibliographical references (pages 361-368) and index. |
| Contents |
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. |
| Summary |
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 |
| Subject |
Data mining
|
|
Big data
|
|
Information science
|
|
Business -- Data processing
|
| Added Author |
Fawcett, Tom
|
| Cover Title |
What you need to know about data mining and data-analytic thinking |
| ISBN |
1449361323 |
|
9781449361327 |
|
