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Practical machine learning with H2O: powerful, scalable techniques for deep learning and AI

✍ Scribed by Cook, Darren

Publisher
O'Reilly Media
Year
2017;2016
Tongue
English
Edition
First edition
Category
Library
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✦ Synopsis

Learn how to construct machine learning and data analysis scalable for big data using H2O software, using sample data sets and several machine-learning techniques including deep learning, random forests, unsupervised learning and ensemble learning.;Installation and quick-start -- Data import, data export -- The data sets -- Common model parameters -- Random forest -- Gradient boosting machines -- Linear models -- Deep learning (neural nets) -- Unsupervised learning -- Everything else -- Epilogue: Didn't they all do well!

✦ Table of Contents

Installation and quick-start --
Data import, data export --
The data sets --
Common model parameters --
Random forest --
Gradient boosting machines --
Linear models --
Deep learning (neural nets) --
Unsupervised learning --
Everything else --
Epilogue: Didn't they all do well!

✦ Subjects

Artificial intelligence;Computer simulation;H2O (Computer software);Machine learning

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