// 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