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Ensemble Methods for Machine Learning
Taschenbuch von Gautam Kunapuli
Sprache: Englisch

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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.
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.
Über den Autor
Gautam Kunapuli has over 15 years of experience in academia and the machine learning industry. He has developed several novel algorithms for diverse application domains including social network analysis, text and natural language processing, behaviour mining, educational data mining and biomedical applications. He has also published papers exploring ensemble methods in relational domains and with imbalanced data.
Details
Erscheinungsjahr: 2023
Genre: Importe, Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781617297137
ISBN-10: 1617297135
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Kunapuli, Gautam
Hersteller: Manning
Verantwortliche Person für die EU: Manning, St.-Martin-Straße 82, D-81541 München, salesde@pearson.com
Maße: 231 x 185 x 20 mm
Von/Mit: Gautam Kunapuli
Erscheinungsdatum: 02.06.2023
Gewicht: 0,646 kg
Artikel-ID: 120533929
Über den Autor
Gautam Kunapuli has over 15 years of experience in academia and the machine learning industry. He has developed several novel algorithms for diverse application domains including social network analysis, text and natural language processing, behaviour mining, educational data mining and biomedical applications. He has also published papers exploring ensemble methods in relational domains and with imbalanced data.
Details
Erscheinungsjahr: 2023
Genre: Importe, Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781617297137
ISBN-10: 1617297135
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Kunapuli, Gautam
Hersteller: Manning
Verantwortliche Person für die EU: Manning, St.-Martin-Straße 82, D-81541 München, salesde@pearson.com
Maße: 231 x 185 x 20 mm
Von/Mit: Gautam Kunapuli
Erscheinungsdatum: 02.06.2023
Gewicht: 0,646 kg
Artikel-ID: 120533929
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