H2O Documentation
  • New Users
    • Getting Started From a Downloaded Zip File
    • Command-line Options
  • H2O User Guide
    • General
    • Data
    • Model
    • Score
    • Admin
    • Help
  • Tutorials For Web UI
    • GLM Tutorial
    • GLM Grid Tutorial
    • K Means Tutorial
    • Random Forest Tutorial
    • PCA Tutorial
    • GBM Tutorial
    • GBM Grid Tutorial
    • Multimodel Scoring Tutorial
    • Quick Start Videos
  • Data Science in H2O
    • Generalized Linear Model
    • K-Means
    • Random Forest
    • Principal Components Analysis
    • Summary
    • Gradient Boosted Regression and Classification
    • Naive Bayes
    • Deep Learning
    • Data Science and Machine Learning
    • Stochastic Gradient Descent
    • References
  • R On H2O
    • Install H2O package in R
    • R Package Documentation
    • R Tutorial
  • Tableau on H2O
    • Tableau 8.1
    • Tableau 8.2
  • H2O on EC2
    • EC2 Glossary
    • Launch H2O from Command Line
    • Launch H2O from AWS Console
  • H2O on Hadoop
    • Hadoop Glossary
    • Running H2O on Hadoop
    • Hadoop White Paper
  • H2O on a Multi-Node Cluster
  • Getting Started with Development in H2O
    • From Source Code (Github)
    • Updating H2O from Github
    • H2O For Eclipse Users (Github)
    • For IDEA Users (Github)
    • Setting up an H2O Hadoop cluster on a Mac
    • Scala for H2O: Shalala
    • Java API
    • REST/JSON API
    • H2O Developer Cookbook
  • H2O Software Architecture
    • H2O Software Stack
    • How R Scripts Call H2O GLM
    • How R Expressions are Sent to H2O for Evaluation
    • Parse Overview
    • Job/MRTask/FJTask Overview
  • H2O Algorithms Roadmap
  • H2O Performance Datasheet
  • Benchmarks
  • Public Data Sets
    • Open City Datasets
    • Transportation and Travel
    • Sciences and Engineering
    • Diverse Data Sets
    • Public Policy Data
    • Other
  • Glossary
  • Index By Subject
  • Troubleshooting H2O
    • General Issues
    • Algorithm Issues
    • R and H2O
    • Hadoop and H2O
    • EC2 and H2O
  • H2O Community
    • Contact Us
    • Join the open-source family
    • H2O License
  • High Availability Considerations for H2O
 
H2O Documentation
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  • Index By Subject
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Index By SubjectΒΆ

Algorithms Roadmap

  • H2O Algorithms Roadmap

Benchmarks

  • Benchmarks

Classification

  • Random Forest
  • Naive Bayes
  • K-Means

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
  • Command-line Options

K-Means

  • K-Means
  • K Means Tutorial

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

  • R On H2O

R Package Document

  • R Package Documentation

Random Forest

  • Random Forest

References

  • References

Scala

Stochastic Gradient Descent

  • Stochastic Gradient Descent

Summary (summary statistics on data)

  • Summary

Tutorials

  • GLM Tutorial
  • GLM Grid Tutorial
  • K Means Tutorial
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