Hands-On Ensemble Learning with Python
Kyriakides, George, G. Margaritis, Konstantinos
- 出版商: Packt Publishing
- 出版日期: 2019-07-24
- 售價: $1,680
- 貴賓價: 9.5 折 $1,596
- 語言: 英文
- 頁數: 298
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1789612853
- ISBN-13: 9781789612851
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相關分類:
Python、程式語言
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相關翻譯:
集成式學習:Python 實踐!整合全部技術,打造最強模型 (Hands-On Ensemble Learning with Python: Build highly optimized ensemble machine learning models using scikit-learn and Keras) (繁中版)
商品描述
Ensembling is a technique of combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior predictive power. This book will demonstrate how you can use a variety of weak algorithms to make a strong predictive model.
With its hands-on approach, you'll not only get up to speed with the basic theory but also the application of different ensemble learning techniques. Using examples and real-world datasets, you'll be able to produce better machine learning models to solve supervised learning problems such as classification and regression. In addition to this, you'll go on to leverage ensemble learning techniques such as clustering to produce unsupervised machine learning models. As you progress, the chapters will cover different machine learning algorithms that are widely used in the practical world to make predictions and classifications. You'll even get to grips with the use of Python libraries such as scikit-learn and Keras for implementing different ensemble models.
By the end of this book, you will be well-versed in ensemble learning, and have the skills you need to understand which ensemble method is required for which problem, and successfully implement them in real-world scenarios.