Автор: Gautam Kunapuli
Издательство: Manning Publications
Год: 2022
Страниц: 320
Язык: английский
Формат: pdf (true)
Размер: 19.4 MB
In Ensemble Methods for Machine Learning you'll learn to implement the most important ensemble machine learning methods from scratch.
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.
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