Isbn: 9781491964606 - practical machine learning with h20: powerful, scalable techniques for deep learning and ai (23 resultados)

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Paperback or Softback. Condición: New. Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AI. Book.

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Paperback. Condición: Brand New. 200 pages. 9.00x6.75x0.50 inches. In Stock.

Condición: New. This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms. Num Pages: 300 pages, black & white illustrations. BIC Classification: UNC; UYQM. Category: (XV) Technical / Manuals. Dimension: 181 x 233 x 18. Weight in Grams: 514. . 2016. 1st Edition. Paperback. . . . . …

Condición: New. In English.

Condición: New. This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms. Num Pages: 300 pages, black & white illustrations. BIC Classification: UNC; UYQM. Category: (XV) Technical / Manuals. Dimension: 181 x 233 x 18. Weight in Grams: 514. . 2016. 1st Edition. Paperback. . . . . Books ship from the US and Ireland. …

Condición: New. This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms.&Uumlber den AutorrnrnDarren Cook has over 20 years of experience as a software developer, data analyst, and technical d.

Taschenbuch. Condición: Neu. Neuware - 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.…

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