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Tutorials and training material for the H2O Machine Learning Platform
This document contains tutorials and training materials for H2O-3. If you find any problems with the tutorial code, please open an issue in this repository.
Finding tutorial material in Github
There are a number of tutorials on all sorts of topics in this repo. To help you get started, here are some of the most useful topics in both R and Python.
- Intro to H2O in R
- H2O Grid Search & Model Selection in R
- H2O Deep Learning in R
- H2O Stacked Ensembles in R
- H2O AutoML in R
- LatinR 2019 H2O Tutorial (broad overview of all the above topics)
- Intro to H2O in Python
- H2O Grid Search & Model Selection in Python
- H2O Stacked Ensembles in Python
- H2O AutoML in Python
Most current material
Tutorials in the master branch are intended to work with the lastest stable version of H2O.
|Latest stable H2O release||http://h2o.ai/download|
Tutorial versions in named branches are snapshotted for specific events. Scripts should work unchanged for the version of H2O used at that time.
H2O World 2017 Training
|Wheeler-2 H2O release||http://h2o-release.s3.amazonaws.com/h2o/rel-wheeler/2/index.html|
H2O World 2015 Training
|Tibshirani-3 H2O release||http://h2o-release.s3.amazonaws.com/h2o/rel-tibshirani/3/index.html|
For most tutorials using Python you can install dependent modules to your environment by running the following commands.
# As current user pip install -r requirements.txt
# As root user sudo -E pip install -r requirements.txt
Note: If you are behind a corporate proxy you may need to set environment variables for
# If you are behind a corporate proxy export https_proxy=https://<user>:<password>@<proxy_server>:<proxy_port> # As current user pip install -r requirements.txt
# If you are behind a corporate proxy export https_proxy=https://<user>:<password>@<proxy_server>:<proxy_port> # As root user sudo -E pip install -r requirements.txt