|aPractical machine learning with H2O :|bpowerful, scalable techniques for AI and deep learning /|cDarren Cook.
|aMachine learning with H2O
|aSebastopol, CA :|bO'Reilly Media,|cc2017.
|axv, 281 p. :|bill. ;|c24 cm.
|aAn introduction to the open-source machine learning package explains how to install H2O, import and export data, and distinguish H2O algorithms, and explores such machine learning techniques as deep learning, random forests, and ensemble learning.
In Practical Machine Learning with H2O.ai, author Darren Cook introduces readers to H2O, an open-source machine learning package that is gaining popularity in the data science community. This concise book will first teach readers how to install H2O, import and export data, and distinguish H2O algorithms. Readers will then explore various modern machine learning techniques such as deep learning, random forests, unsupervised learning, and ensemble learning. Throughout the chapters, machine learning models are introduced and tried on the same 3 data sets, guiding readers through the process of finding the right parameters for a given data set.