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Scalable Machine Learning
For Smarter Applications
Who am I?
Hank Roark (hank@h2oai.com, @hankroark)
Data Scientist & Hacker @ H2O.ai
Lecturer in Systems Thinking, UIUC
13 years at John Deere doing Research, New Product
Development, New High Tech Ventures
Previously at startups and consulting
Physics Georgia Tech

Systems Design & Management MIT
• Founded: 2011 venture-backed, debuted in 2012
• Product: H2O open source in-memory prediction engine
• Team: 37 - Distributed Systems Engineers doing ML
• HQ: Mountain View, CA
H2O.ai Overview
H2O.ai

Machine Intelligence
25,000 commits / 3yrs
H2O World Conference 2014
Team Work @ H2O.ai
28
Join H2O World Nov 9-11 2015!
What is H2O?
Math Platform
• Open
source in-
memory
prediction
engine
• Parallelized
and
distributed
algorithms
making the
most use
API
• Easy to
use and
adopt
• Written in
Java –
perfect for
Java
Programmer
s
• REST API
(JSON) –
Big Data
• More data?
Or better
models?
BOTH
• Use all of
your data –
model
without
down
sampling
• Run a
H2O.ai

Machine Intelligence
Accuracy with Speed and Scale
H2O.ai

Machine Intelligence
H2O Software Stack
JavaScript R Python Excel/Tableau
Network
Rapids Expression Evaluation
Engine
Scala
Customer
Algorithm
Customer
Algorithm
Parse
GLM
GBM
RF
Deep Learning
K-Means
PCA
In-H2O Prediction
Engine
Fluid Vector Frame
Distributed K/V Store
Non-blocking Hash Map
Job
MRTask
Fork/Join
Flow
Customer Algorithm
Spark Hadoop Standalone H2O
H2O.ai

Machine Intelligence
Reading Data from HDFS into H2O with R
STEP 1
R user
h2o_df = h2o.importFile(“hdfs://path/to/data.csv”)
H2O.ai

Machine Intelligence
Reading Data from HDFS into H2O with R
H2O
H2O
H2O
data.csv
HTTP REST API
request to H2O
has HDFS path
H2O ClusterInitiate distributed
ingest
HDFS
Request data
from HDFS
STEP 2
2.2
2.3
2.4
R
h2o.importFile()
2.1
R function call
H2O.ai

Machine Intelligence
Reading Data from HDFS into H2O with R
H2O
H2O
H2O
R
HDFS
STEP 3
Cluster IP
Cluster Port
Pointer to Data
Return pointer to
data in REST API
JSON Response
HDFS provides
data
3.3
3.4
3.1h2o_df object
created in R
data.csv
h2o_df
H2O
Frame
3.2
Distributed H2O
Frame in DKV
H2O Cluster
H2O.ai

Machine Intelligence
R Script Starting H2O GLM
HTTP
REST/JSON
.h2o.startModelJob()
POST /3/ModelBuilders/glm
h2o.glm()
R script
Standard R process
TCP/IP
HTTP
REST/JSON
/3/ModelBuilders/glm endpoint
Job
GLM algorithm
GLM tasks
Fork/Join
framework
K/V store
framework
H2O process
Network layer
REST layer
H2O - algos
H2O - core
User process
H2O process
Legend
H2O.ai

Machine Intelligence
R Script Retrieving H2O GLM Result
HTTP
REST/JSON
h2o.getModel()
GET /3/Models/glm_model_id
h2o.glm()
R script
Standard R process
TCP/IP
HTTP
REST/JSON
/3/Models endpoint
Fork/Join
framework
K/V store
framework
H2O process
Network layer
REST layer
H2O - algos
H2O - core
User process
H2O process
Legend
Step 1
• Download and install h2o: h2o.ai, hit download
button
• Only requirement is JDK 1.7+
• plus required packages if using R or Python
• Pick R, Python (2.7.x), or Standalone for tonight
13
Step 2
• http://bit.ly/1hyn5ag
• Contains training and validation data,
starter R and Python scripts
• Unzip mountainview.zip
14
Thank You
Text ‘H2OINTRO’ to 33444 to receive the content 

from this presentation

(final holdout test set for Mountain View Meetup is at 

https://s3.amazonaws.com/0xdata-public/hank/madbum.csv)

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Introduction to Data Science with H2O- Mountain View

  • 1. Scalable Machine Learning For Smarter Applications
  • 2. Who am I? Hank Roark (hank@h2oai.com, @hankroark) Data Scientist & Hacker @ H2O.ai Lecturer in Systems Thinking, UIUC 13 years at John Deere doing Research, New Product Development, New High Tech Ventures Previously at startups and consulting Physics Georgia Tech
 Systems Design & Management MIT
  • 3. • Founded: 2011 venture-backed, debuted in 2012 • Product: H2O open source in-memory prediction engine • Team: 37 - Distributed Systems Engineers doing ML • HQ: Mountain View, CA H2O.ai Overview H2O.ai
 Machine Intelligence
  • 4. 25,000 commits / 3yrs H2O World Conference 2014 Team Work @ H2O.ai 28 Join H2O World Nov 9-11 2015!
  • 5. What is H2O? Math Platform • Open source in- memory prediction engine • Parallelized and distributed algorithms making the most use API • Easy to use and adopt • Written in Java – perfect for Java Programmer s • REST API (JSON) – Big Data • More data? Or better models? BOTH • Use all of your data – model without down sampling • Run a H2O.ai
 Machine Intelligence
  • 7. H2O.ai
 Machine Intelligence H2O Software Stack JavaScript R Python Excel/Tableau Network Rapids Expression Evaluation Engine Scala Customer Algorithm Customer Algorithm Parse GLM GBM RF Deep Learning K-Means PCA In-H2O Prediction Engine Fluid Vector Frame Distributed K/V Store Non-blocking Hash Map Job MRTask Fork/Join Flow Customer Algorithm Spark Hadoop Standalone H2O
  • 8. H2O.ai
 Machine Intelligence Reading Data from HDFS into H2O with R STEP 1 R user h2o_df = h2o.importFile(“hdfs://path/to/data.csv”)
  • 9. H2O.ai
 Machine Intelligence Reading Data from HDFS into H2O with R H2O H2O H2O data.csv HTTP REST API request to H2O has HDFS path H2O ClusterInitiate distributed ingest HDFS Request data from HDFS STEP 2 2.2 2.3 2.4 R h2o.importFile() 2.1 R function call
  • 10. H2O.ai
 Machine Intelligence Reading Data from HDFS into H2O with R H2O H2O H2O R HDFS STEP 3 Cluster IP Cluster Port Pointer to Data Return pointer to data in REST API JSON Response HDFS provides data 3.3 3.4 3.1h2o_df object created in R data.csv h2o_df H2O Frame 3.2 Distributed H2O Frame in DKV H2O Cluster
  • 11. H2O.ai
 Machine Intelligence R Script Starting H2O GLM HTTP REST/JSON .h2o.startModelJob() POST /3/ModelBuilders/glm h2o.glm() R script Standard R process TCP/IP HTTP REST/JSON /3/ModelBuilders/glm endpoint Job GLM algorithm GLM tasks Fork/Join framework K/V store framework H2O process Network layer REST layer H2O - algos H2O - core User process H2O process Legend
  • 12. H2O.ai
 Machine Intelligence R Script Retrieving H2O GLM Result HTTP REST/JSON h2o.getModel() GET /3/Models/glm_model_id h2o.glm() R script Standard R process TCP/IP HTTP REST/JSON /3/Models endpoint Fork/Join framework K/V store framework H2O process Network layer REST layer H2O - algos H2O - core User process H2O process Legend
  • 13. Step 1 • Download and install h2o: h2o.ai, hit download button • Only requirement is JDK 1.7+ • plus required packages if using R or Python • Pick R, Python (2.7.x), or Standalone for tonight 13
  • 14. Step 2 • http://bit.ly/1hyn5ag • Contains training and validation data, starter R and Python scripts • Unzip mountainview.zip 14
  • 15. Thank You Text ‘H2OINTRO’ to 33444 to receive the content 
 from this presentation (final holdout test set for Mountain View Meetup is at 
 https://s3.amazonaws.com/0xdata-public/hank/madbum.csv)