Data science for business /
"This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. By learning data science principles, y...
Guardado en:
| Autor principal: | |
|---|---|
| Otros Autores: | |
| Formato: | Libro |
| Lenguaje: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly,
2013.
|
| Edición: | 1st ed. |
| Materias: | |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
| LEADER | 02165cam a2200337Ia 4500 | ||
|---|---|---|---|
| 001 | 99743428504151 | ||
| 005 | 20190527154351.0 | ||
| 008 | 130620s2013 caua b 001 0 eng d | ||
| 020 | |a 9781449361327 | ||
| 020 | |a 1449361323 | ||
| 035 | |a (OCoLC)962030452 | ||
| 035 | |a (OCoLC)ocn962030452 | ||
| 040 | |a ERL |c ERL |d OCLCO |d OCLCF |d OCLCQ |d OCLCO |d TJC |d U@S | ||
| 049 | |a U@SA | ||
| 050 | 4 | |a QA76.9.D343 |b P76 2013 | |
| 082 | 0 | 4 | |a 006.312 |2 23 |
| 100 | 1 | |a Provost, Foster, |d 1964- | |
| 245 | 1 | 0 | |a Data science for business / |c Foster Provost and Tom Fawcett. |
| 250 | |a 1st ed. | ||
| 260 | |a Sebastopol, CA : |b O'Reilly, |c 2013. | ||
| 300 | |a xxi, 386 p. : |b il. ; |c 23 cm. | ||
| 504 | |a Incluye referencias bibliográficas e índice. | ||
| 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 -- Proposal review guide -- Another sample proposal. | |
| 520 | |a "This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. By learning data science principles, you will understand the many data mining techniques in use today. More importantly, these principles underpin the processes and strategies necessary to solve business problems through data mining techniques"--Contratapa. | ||
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Big data. | |
| 650 | 0 | |a Business |x Data processing. | |
| 650 | 7 | |a Minería de datos. |2 UDESA | |
| 650 | 7 | |a Grandes volúmenes de datos. |2 UDESA | |
| 650 | 7 | |a Negocios |x Procesamiento de datos. |2 UDESA | |
| 700 | 1 | |a Fawcett, Tom. | |