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Beschreibung
Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real-world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models.
Details
| Verlag | Manning |
| Ersterscheinung | 02. Mai 2023 |
| Maße | 23.1 cm x 18.5 cm x 2 cm |
| Gewicht | 646 Gramm |
| Format | Softcover |
| ISBN-13 | 9781617297137 |
| Seiten | 352 |
Schlagwörter
EDV / Theorie / Programmieren / Allgemeines, EDV / Theorie / Software-Entw. / Software Engineering, Fuzzy Logik - Fuzzy Set, Intelligenz / Künstliche Intelligenz, KI, Künstliche Intelligenz - AI, Maschinelles Lernen, Neuronale Netze und Fuzzysysteme, Neuronales Netz - Neuronaler Computer - Neurocomputer, Programmier- und Skriptsprachen - allgemein, Programmiersprachen, Programmiertechniken, Software Engineering
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