// Databricks notebook source exported at Tue, 28 Jun 2016 09:30:18 UTC

Scalable Data Science

prepared by Raazesh Sainudiin and Sivanand Sivaram

supported by and

The html source url of this databricks notebook and its recorded Uji :

Deep learning with H2O.ai and Spark

• This notebook provides an introduction to the use of Deep Learning algorithms with H2O.ai and Spark
• It introduces H2O.ai a distributed machine learning framework
• It shows an example deep learning application written in H2O.ai (Sparkling water) and Spark

H2O features - overview

http://www.h2o.ai/product/downloads/recommended-systems.pdf ***

• H2O Core
• H2O Flow
• Algorithms
• Sparkling Water
• H2O Frame

###H2O.ai - Architecture
https://github.com/h2oai/h2o-3/blob/master/h2o-docs/src/product/architecture/Architecture.md

– Image Credit: Sparkling water

H2O Flow

Watch later (2:28 seconds):

###Algorithms

####Supervised Learning

• Generalized Linear Modeling (GLM): Tutorial

  Reference

• Gradient Boosting Machine (GBM): Tutorial

  Reference

• Deep Learning: Tutorial

  Reference

• Ensembles (Stacking): Tutorial

  Reference

• Distributed Random Forest: Tutorial
• Naive Bayes: Reference ***

####Unsupervised Learning

• Generalized Low Ranked Modeling (GLRM): Tutorial

  Reference

• K-Means: Tutorial
• PCA: Tutorial
• Anomaly Detection via Deep Learning: Tutorial

###H2O.ai - Sparkling water
https://github.com/h2oai/sparkling-water/blob/master/DEVEL.md

– Image Credit: Sparkling water

#####Data sharing between RDD, DataFrame and H2OFrame

– Image Credit: Sparkling water

APIs

• Core API
• Algorithms
• Models
  ***

Deep learning booklet

Scalable Data Science

prepared by Raazesh Sainudiin and Sivanand Sivaram

supported by and