Index By Subject¶

Algorithms Roadmap

• H2O Algorithms Roadmap

Benchmarks

• Benchmarks

Classification

• Random Forest
• Naive Bayes
• K-Means

Contact H2O

• Contact Us

Data Science

• Data Science in H2O

Data

• Summary

Deep Learning

• Deep Learning

Development

• Getting Started with Development in H2O

Downloads

• Getting Started From a Downloaded Zip File

Eclipse

• H2O For Eclipse Users (Github)

Generalized Linear Modeling

• Generalized Linear Model
• GLM Tutorial

Gradient Boosted Models

• Gradient Boosted Regression and Classification
• GLM Grid Tutorial

Hadoop

• H2O on Hadoop
• Setting up an H2O Hadoop cluster on a Mac

High Availability

• High Availability Considerations for H2O

Idea

• For IDEA Users (Github)

Java

• Java API
• H2O Command-line Options

K-Means

• K-Means
• K Means Tutorial

License

• H2O License

Machine Learning

• Data Science and Machine Learning

Multinode

• H2O on a Multi-Node Cluster

Naive Bayes

• Naive Bayes

Principal Components Analysis

• Principal Components Analysis

R Console

• H2O Installation in R From Download Table
• H2O + R For Developers Using Github

R

• Documentation For R Users (Console and Studio)

R Package Document

• R Package Documentation

R Studio

• H2O Installation in R From Download Table
• H2O + R For Developers Using Github

Random Forest

• Random Forest

References

• References

Scala

Stochastic Gradient Descent

• Stochastic Gradient Descent

Summary (summary statistics on data)

• Summary

Troubleshooting

• Troubleshooting H2O

Tutorials

• GLM Tutorial
• GLM Grid Tutorial
• K Means Tutorial