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Hands-On Automated Machine Learning

You're reading from  Hands-On Automated Machine Learning

Product type Book
Published in Apr 2018
Publisher Packt
ISBN-13 9781788629898
Pages 282 pages
Edition 1st Edition
Languages
Authors (2):
Sibanjan Das Sibanjan Das
Profile icon Sibanjan Das
Umit Mert Cakmak Umit Mert Cakmak
Profile icon Umit Mert Cakmak
View More author details
Toc

Table of Contents (10) Chapters close

Preface 1. Introduction to AutoML 2. Introduction to Machine Learning Using Python 3. Data Preprocessing 4. Automated Algorithm Selection 5. Hyperparameter Optimization 6. Creating AutoML Pipelines 7. Dive into Deep Learning 8. Critical Aspects of ML and Data Science Projects 9. Other Books You May Enjoy

Ensemble methods

Ensembling models are a robust approach to enhancing the efficiency of the predictive models. It is a well-thought out strategy that is very similar to a power-packed word—TEAM !! Any task done by a team leads to significant accomplishments.

What are ensemble models?

Likewise, in the ML world, an ensemble model is a team of models operating together to enhance the result of their work. Technically, ensemble models comprise of several supervised learning models that are individually trained, and the results are merged in various ways to achieve the final prediction. This result has higher predictive power than the results of any of its constituting learning algorithms independently.

Mostly, there are...

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