| 000 | 01215 a2200181 4500 | ||
|---|---|---|---|
| 003 | OSt | ||
| 005 | 20250807020005.0 | ||
| 008 | 250730b |||||||| |||| 00| 0 eng d | ||
| 020 | _a9781119828792 | ||
| 082 |
_a658.403 _bM184 |
||
| 245 |
_aMachine learning for business analytics _bconcepts, techniques and applications in rapidminer _cGalit Shmueli ...[et al.] |
||
| 260 |
_bJohn Wiley _c2023 _aHoboken |
||
| 300 | _axxix, 699p | ||
| 520 | _aMachine Learning for Business Analytics: Concepts, Techniques and Applications in RapidMiner provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. | ||
| 650 |
_aBusiness data processing _aData mining _aMachine learning _aRapidminer _aBusiness analytics |
||
| 700 |
_aShmueli, Galit _aBruce, Peter C. _aDeokar, Amit V. _aPatel, Nitin R. |
||
| 942 |
_cBK _01 |
||
| 999 |
_c567587 _d567587 |
||