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- Дата: 5-04-2023, 16:18
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Автор: Gautam Kunapuli
Издательство: Manning Publications
Год: 2023
Страниц: 354
Язык: английский
Формат: pdf (true)
Размер: 18.7 MB
Ensemble Machine Learning combines the power of multiple Machine Learning approaches, working together to deliver models that are highly performant and highly accurate. Ensemble Machine Learning trains a diverse group of Machine Learning models to work together, aggregating their output to deliver richer results than a single model. Now in Ensemble Methods for Machine Learning you’ll discover core ensemble methods that have proven records in both Data Science competitions and real-world applications. Hands-on case studies show you how each algorithm works in production. By the time you're done, you'll know the benefits, limitations, and practical methods of applying Ensemble Machine Learning to real-world data, and be ready to build more explainable ML systems. For Python programmers with Machine Learning experience.