This document discusses H2O.ai, an open source in-memory machine learning platform. It can perform distributed machine learning on large datasets using algorithms like generalized linear modeling, gradient boosted machines, random forests, and deep learning. The platform provides APIs and interfaces for R, Python, Scala, Spark, and other languages. It can handle big data from sources like HDFS, S3, and NFS without sampling. The document includes an overview of H2O's architecture and demonstrates its use on a bike sharing dataset with over 10 million rows.

1. H2O.ai
Machine Intelligence
Fast, Scalable In-Memory Machine and Deep Learning
For Smarter Applications
Python with H2O
Cliff Click

2. H2O.ai
Machine Intelligence
Who Am I?
Cliff Click
CTO, Co-Founder H2O.ai
cliff@h2o.ai
40 yrs coding
35 yrs building compiler
30 yrs distributed computation
20 yrs OS, device drivers, HPC, HotSpot
10 yrs Low-latency GC, custom java hardware,
NonBlockingHashMap
20 patents, dozens of papers
100s of public talks
PhD Computer Science
1995 Rice University
HotSpot JVM Server Compiler
“showed the world JITing is possible”

3. H2O.ai
Machine Intelligence
H2O Open Source In-Memory
Machine Learning for Big Data
Distributed In-Memory Math Platform
GLM, GBM, RF, K-Means, PCA, Deep Learning
Easy to use SDK & API
Java, R/CRAN, Scala, Spark, Python, JSON, Browser GUI
Use ALL your data
Modeling without sampling
HDFS, S3, NFS, NoSql
Big Data & Better Algorithms
Better Predictions!

4. H2O.ai
Machine Intelligence
TBD.
Customer
Support
TBD
Head of
Sales
Distributed
Systems
Engineers
Making
ML Scale!

5. H2O.ai
Machine Intelligence
Practical Machine Learning
Value Requirements
Fast & Interactive In-Memory
Big Data (No Sampling) Distributed
Ownership Open Source
Extensibility API/SDK
Portability Java, REST/JSON
Infrastructure Cloud or On-Premise Hadoop
or Private Cluster

6. H2O.ai
Machine Intelligence
H2O Architecture
Prediction Engine
R & Exec Engine
Web Interface
Spark Scala REPL
Nano-Fast
Scoring Engine
Distributed
In-Memory K/V Store
Column Compress Data
Map/Reduce
Memory Manager
Algorithms!
GBM, Random Forest,
GLM, PCA, K-Means,
Deep Learning
HDFS S3 NFS

7. H2O.ai
Machine Intelligence
H2O Architecture
Prediction Engine
R & Exec Engine
Web Interface
Spark Scala REPL
Nano-Fast
Scoring Engine
Distributed
In-Memory K/V Store
Column Compress Data
Map/Reduce
Memory Manager
Algorithms!
GBM, Random Forest,
GLM, PCA, K-Means,
Deep Learning
HDFS S3 NFS

8. H2O.ai
Machine Intelligence
Demo!
Python Demo
●
CitiBike of NYC
●
Predict bikes-per-hour-per-station
– From per-trip logs
●
10M rows of data
●
Group-By, date/time feature-munging

9. H2O.ai
Machine Intelligence
H2O: A Platform for Big Math
●
Most Any Java on Big 2-D Tables
– Write like its single-thread POJO code
– Runs distributed & parallel by default
●
Fast: billion row logistic regression takes 4 sec
●
Worlds first parallel & distributed GBM
– Plus GBM, Deep Learn / Neural Nets, RF, PCA, GLM...
●
R integration: use terabyte datasets from R
●
Sparkling Water: Direct Spark integration

10. H2O.ai
Machine Intelligence
H2O: A Platform for Big Math
●
Easy launch: “java -jar h2o.jar”
– No GC tuning: -Xmx as big as you like
●
Production ready:
– Private on-premise cluster OR
– In the Cloud
– Hadoop, Yarn, EC2, or standalone cluster
– HDFS, S3, NFS, URI & other datasources
– Open Source, Apache v2