Items related to Ensemble Methods for Machine Learning
- PublisherManning
- Publication date2023
- ISBN 10 1617297135
- ISBN 13 9781617297137
- BindingPaperback
- LanguageEnglish
- Number of pages352
- Rating
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Ensemble Methods for Machine Learning
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Ensemble Methods for Machine Learning
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Ensemble Methods for Machine Learning
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Ensemble Methods for Machine Learning
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Ensemble Methods for Machine Learning (Paperback or Softback)
Published by
Manning Publications 5/2/2023, 2023
ISBN 10: 1617297135
ISBN 13: 9781617297137
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Ensemble Methods for Machine Learning
Published by
Manning Publications, 2023
ISBN 10: 1617297135
ISBN 13: 9781617297137
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Ensemble Methods for Machine Learning (Paperback)
Published by
Manning Publications, New York, 2023
ISBN 10: 1617297135
ISBN 13: 9781617297137
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Paperback. Condition: new. Paperback. 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. About the Technology Ensemble machine learning lets you make robust predictions without needing the huge datasets and processing power demanded by deep learning. It sets multiple models to work on solving a problem, combining their results for better performance than a single model working alone. This "wisdom of crowds" approach distils information from several models into a set of highly accurate results. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781617297137
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