Free Ebook Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AI, by Darren Cook
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Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AI, by Darren Cook
Free Ebook Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AI, by Darren Cook
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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
- Sales Rank: #144630 in Books
- Brand: imusti
- Published on: 2016-12-16
- Original language: English
- Dimensions: 9.19" h x .63" w x 7.00" l, .0 pounds
- Binding: Paperback
- 300 pages
- O\'Reilly Media
About the Author
Darren Cook has over 20 years of experience as a software developer, data analyst, and technical director, working on everything from financial trading systems to NLP, data visualization tools, and PR websites for some of the world’s largest brands. He is skilled in a wide range of computer languages, including R, C++, PHP, JavaScript, and Python. He works at QQ Trend, a financial data analysis and data products company.
Most helpful customer reviews
1 of 1 people found the following review helpful.
great first book on H2O machine learning open source framework.
By Gruyer Francois
This seems to be the very first book on this ML framework (H2O). And is is just great.
The book is crystal clear and extremely comprehensive, very easy to read, with examples you can reproduce easily (datasets are on line in a public Git repo).
It covers a very practical ground on the 4 main algorithms implemented in H2O cluster: RandomForest, GBM, GLM, and last but not least : deep learning...
"Practical" means explanations are strongly grounded on a set of 4 datasets , the author plays with, explaining both their preparation , analysis with H2O (code is both in R and PYTHON), and a great deal of time is spent on very useful considerations on how to 'tune' the various algorithms
to obtain better models, comparing their effectiveness.
All this in very clear style and explanations.
A must have for everyone interested in implementing ML features concretely.
Francois GRUYER
(from Paris, France)
0 of 0 people found the following review helpful.
great machine learning book
By manuel
This book is an ample introduction of H2O for R and Python practitioners. Those interested in state-of-the-art machine learning and deep learning approaches will enjoy this book completely, whether they are beginners or proficient R and Python users for statistical analysis. The author makes clear descriptions and his explanations are always accessible. His high-quality sense of humour interspersed throughout the text helps maintain the interest in the text as one reads. I would love to read more of this author.
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