Practical machine learning with H2o : powerful, scalable techniques for deep learning and ai / / Darren Cook

• Autore: Cook Darren
• Pubblicazione: Beijing, [China] : , : O'Reilly, , 2017; ©2017
• Edizione: First edition.
• Descrizione fisica: 1 online resource (300 pages) : illustrations
• Disciplina: 006.31
• Soggetto topico: Machine learning - Development
• Note generali: Includes index.
• Sommario/riassunto: Machine learning has finally come of age. With H2O software, you can perform machine learning and data analysis using a simple open source framework that’s easy to use, has a wide range of OS and language support, and scales for big data. This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms. If you’re familiar with R or Python, know a bit of statistics, and have some experience manipulating data, author Darren Cook will take you through H2O basics and help you conduct machine-learning experiments on different sample data sets. You’ll explore several modern machine-learning techniques such as deep learning, random forests, unsupervised learning, and ensemble learning. Learn how to import, manipulate, and export data with H2O Explore key machine-learning concepts, such as cross-validation and validation data sets Work with three diverse data sets, including a regression, a multinomial classification, and a binomial classification Use H2O to analyze each sample data set with four supervised machine-learning algorithms Understand how cluster analysis and other unsupervised machine-learning algorithms work
• Altri titoli varianti: Machine learning with H2O
• Titolo autorizzato: Practical machine learning with H2o
• ISBN: 1-4919-6455-3; 1-4919-6459-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910155158803321
• Lo trovi qui: Univ. Federico II