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Can I read Hands-On Ensemble Learning with Python : Build Highly Optimized Ensemble Machine Learning Models Using Scikit-learn and Keras on EtoBox?
Hands-On Ensemble Learning with Python : Build Highly Optimized Ensemble Machine Learning Models Using Scikit-learn and Keras by George Kyriakides, Konstantinos G. Margaritis is a nonfiction available to read on EtoBox.
What is Hands-On Ensemble Learning with Python : Build Highly Optimized Ensemble Machine Learning Models Using Scikit-learn and Keras about?
Combine popular machine learning techniques to create ensemble models using Python Key Features Implement ensemble models using algorithms such as random forests and AdaBoost Apply boosting, bagging, and stacking ensemble methods to improve the prediction accuracy of your model Explore real-world data sets and practical examples coded in scikit-learn and Keras Book Description 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 ar
Who reads Hands-On Ensemble Learning with Python : Build Highly Optimized Ensemble Machine Learning Models Using Scikit-learn and Keras?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- George Kyriakides, Konstantinos G. Margaritis
- Publisher
- Packt Publishing, Limited
- Published
- 2019
- Language
- EN
- ISBN
- 9781789617887
- Category
- nonfiction
- Subjects
- Technology, Science, Computer Science
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