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‎SUMMARY.md‎

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* [Introduction](README.md)
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* [Intro to Data Science](tutorials/intro-to-datascience/README.md)
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* [Building a Smarter Application](tutorials/building-a-smarter-application/README.md)
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* [Deep Learning](tutorials/deeplearning/deeplearning.md)
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* [Deep Learning](tutorials/deeplearning/README.md)
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* [GLRM](tutorials/glrm/glrm-tutorial.md)
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* [Hive UDF example](tutorials/hive_udf_template/README.md)
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* [Ensembles: Stacking, Super Learner](tutorials/ensembles-stacking/README.md)

‎cover.jpg‎

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‎resources.md‎

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More information about machine learning with H2O
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- **http://docs.h2o.ai/**: Documentation for H2O and Sparkling Water
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- **https://groups.google.com/forum/#!forum/h2ostream**: Open forum for questions about H2O (Google account required)
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##H2O
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- **Documentation for H2O and Sparkling Water**: http://docs.h2o.ai/
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- **Open forum for questions about H2O (Google account required)**: https://groups.google.com/forum/#!forum/h2ostream
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- **Track or file bug reports for H2O **: https://jira.h2o.ai
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- **GitHub repository for H2O**: https://github.com/h2oai
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##Python
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- **About Python**: https://www.python.org/
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- **Latest Python H2O documentation**: http://h2o-release.s3.amazonaws.com/h2o/latest_stable_Pydoc.html
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##R
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- **About R**: https://www.r-project.org/about.html
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- **Download R**: https://cran.r-project.org/mirrors.html
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- **Latest R API H2O documentation**: http://h2o-release.s3.amazonaws.com/h2o/latest_stable_Rdoc.html
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##Sparkling Water
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- **About Spark**: http://spark.apache.org/
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- **Download Spark**: http://spark.apache.org/downloads.html
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- **Sparkling Water Developer documentation**: https://github.com/h2oai/sparkling-water/blob/master/DEVEL.md

‎tutorials/building-a-smarter-application/BuildingASmarterApplication.pdf‎

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‎tutorials/building-a-smarter-application/BuildingASmarterApplication.pptx‎

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‎tutorials/building-a-smarter-application/README.md‎

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### Slides
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* [PDF](BuildingASmarterApplication.pdf)
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* [Powerpoint](BuildingASmarterApplication.pptx)
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* [PDF](https://github.com/h2oai/h2o-world-2015-training/blob/master/tutorials/building-a-smarter-application/BuildingASmarterApplication.pdf)
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* [PowerPoint](https://github.com/h2oai/h2o-world-2015-training/blob/master/tutorials/building-a-smarter-application/BuildingASmarterApplication.pptx)
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### Code
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‎tutorials/data/smsData.txt‎

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‎tutorials/deeplearning/README.md‎

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‎tutorials/deeplearning/convert.sh‎

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## Turn R Markdown into regular Markdown
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sed -e 's/```{r.*}/```/' deeplearning.Rmd > deeplearning.md
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cp deeplearning.md README.md
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## Turn R Markdown into plain R
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sed -e '1,\%```{r.*}%s:^:#:;/^```/,\%```{r.*}%s:^:#:;/```/d' deeplearning.Rmd > deeplearning.R

‎tutorials/deeplearning/deeplearning.R‎

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plotC(paste0("DL ",epochs," epochs"),
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h2o.deeplearning(1:2,3,spiral,epochs=epochs,
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model_id=as.character(previous)))
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for (epochs in c(200,500,1000)) {
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for (epochs in c(200,500,750,1000)) {
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plotC(paste0("DL ",epochs," epochs"),
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h2o.deeplearning(1:2,3,spiral,epochs=epochs,
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model_id=as.character(epochs),
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#
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#Here's a scalable way to do scatter plots via binning (works for categorical and numeric columns) to get more familiar with the dataset.
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#
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dev.new(noRStudioGD=FALSE) #direct plotting output to a new window
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#dev.new(noRStudioGD=FALSE) #direct plotting output to a new window
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par(mfrow=c(1,1)) # reset canvas
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plot(h2o.tabulate(df, "Elevation", "Cover_Type"))
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plot(h2o.tabulate(df, "Horizontal_Distance_To_Roadways", "Cover_Type"))

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