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H2O.ai

Machine Intelligence
How to Transform your Business
with Artificial Intelligence,

Deep Learning and Machine Learning
Mountain View, June 15 2016
Arno Candel, PhD

Chief Architect
SF Bay ACM Chapter Meetup
H2O.ai

Machine Intelligence
Who Am I?
Arno Candel
Chief Architect,
Physicist & Hacker at H2O.ai
PhD Physics, ETH Zurich 2005
10+ yrs Supercomputing (HPC)
6 yrs at SLAC (Stanford Linear Accelerator)
4.5 yrs Machine Learning
2.5 yrs at H2O.ai
Fortune Magazine Big Data All Star
Follow me @ArnoCandel
2
Who	am	I?
H2O.ai

Machine Intelligence
• What is all this A.I. buzz about?
• What can it do?
• What will it change?
• What can you do?
3
Outline
H2O.ai

Machine Intelligence 4
Overview
Machine Learning (ML)
Artificial Intelligence (A.I.)
Computer Science (CS)
H2O.ai
Deep Learning (DL)
H2O.ai

Machine Intelligence 5
Computer Science (CS)
H2O.ai
The study of automating algorithmic
processes that scale.
A computer scientist specializes in the
theory of computation and the design of
computational systems.
Computer	Science
Wikipedia
H2O.ai

Machine Intelligence 6
Artificial	Intelligence
Artificial Intelligence (A.I.)
Computer Science (CS)
H2O.ai
An ideal "intelligent" machine is a
flexible rational agent that perceives its
environment and takes actions that
maximize its chance of success at an
arbitrary goal.
Wikipedia
H2O.ai

Machine Intelligence 7
Machine	Learning
Machine Learning (ML)
Artificial Intelligence (A.I.)
Computer Science (CS)
H2O.ai
The study and construction of
algorithms that can learn from
and make predictions on data.
Wikipedia
H2O.ai

Machine Intelligence 8
Deep	Learning
Machine Learning (ML)
Artificial Intelligence (A.I.)
Computer Science (CS)
H2O.ai
Deep Learning (DL)
hot hot hot hot hot
H2O.ai

Machine Intelligence 9
Deep	Learning
Deep Learning is a branch of machine learning based on a set of
algorithms that attempt to model high-level abstractions in data
by using multiple processing layers, with complex structures or
otherwise, composed of multiple non-linear transformations.
Or simpler: It powers pretty much all of Google.
Deep Learning (DL)
http://www.wired.com/2016/02/ai-is-changing-the-technology-behind-google-searches/
Wikipedia
hot hot hot hot hot
H2O.ai

Machine Intelligence 10
Example	DL	Model:	Multi-Layer	(Deep)	Artificial	Neural	Network
income
loan amount
credit score
borrower will

not default on loan
borrower will

default on loan
IN: data OUT: prediction
nodes : neuron activations (real numbers) — represent features
arrows : connecting weights (real numbers) — learned during training
: non-linearity x -> f(x) — adds models complexity
from 1970s, now rebranded as DL
H2O.ai

Machine Intelligence 11
Deep	Learning	Pros	and	Cons
• conceptually	simple	
• non	linear	
• highly	flexible	and	configurable	
• learned	features	can	be	extracted	
• can	be	fine-tuned	with	more	data	
• efficient	for	multi-class	problems	
• world-class	at	pattern	recognition
Pros:
• hard	to	interpret	
• theory	not	well	understood	
• slow	to	train	and	score	
• overfits,	needs	regularization	
• many	hyper-parameters	
• inefficient	for	categorical	variables	
• very	data	hungry,	learns	slowly
Cons:
Deep Learning got boosted recently by faster computers
H2O.ai

Machine Intelligence 12
Brief	History	of	A.I.,	ML	and	DL
John McCarthy

Princeton, Bell Labs, Dartmouth, later: MIT, Stanford
1955: “A proposal for the Dartmouth summer
research project on Artificial Intelligence”
with Marvin Minsky (MIT), Claude Shannon 

(Bell Labs) and Nathaniel Rochester (IBM)
http://www.asiapacific-mathnews.com/04/0403/0015_0020.pdf
A step back: A.I. was coined over 60 years ago
H2O.ai

Machine Intelligence 13
1955	proposal	for	the	Dartmouth	summer	research	project	on	A.I.
“We propose that a 2-month, 10-man study of artificial
intelligence be carried out during the summer of 1956 at
Dartmouth College in Hanover, New Hampshire. The study is to
proceed on the basis of the conjecture that every aspect of
learning and any other feature of intelligence can in principle be
so precisely described that a machine can be made to
simulate it. An attempt will be made to find how to make machines
use language, form abstractions and concepts, solve kinds of
problems now reserved for humans, and improve themselves. We
think that a significant advance can be made in one or more
of these problems if a carefully selected group of scientists work on
it together for one summer.”
H2O.ai

Machine Intelligence 14
It took a little longer…
McCarthy invents LISP in 1958, influences ALGOL,
popularizes timesharing, wins Turing Award, Kyoto
Price, National Medal of Science, etc.
A.I.	takes	time
H2O.ai

Machine Intelligence 15
Almost	there!	Or	not?
A few thousand years ago Today: still “plowing” along
https://en.wikipedia.org/wiki/Plough
http://www.processindustryinformer.com/
latest-news/news-events/industry-news/
robot-helps-farmers-monitor-fertiliser-water-
usage
We can automate many tasks, general A.I. is still far away.
H2O.ai

Machine Intelligence 16
Step	1:	Great	Algorithms	+	Fast	Computers
Raw computing power can automate complex tasks!
http://nautil.us/issue/18/genius/why-the-chess-computer-deep-blue-played-like-a-human
Earlier he said: “No computer will ever beat me.”
1997: Playing Chess
(IBM Deep Blue beats Kasparov)
Computer	Science

30	custom	CPUs,	60	billion	moves	in	3	mins
H2O.ai

Machine Intelligence 17
Step	2:	More	Data	+	Real-Time	Processing
http://cs.stanford.edu/group/roadrunner/old/presskit.html
2005: Self-driving Cars

DARPA Grand Challenge, 132 miles
(won by Stanford A.I. lab*)
Sensors	&	Computer	Science

video,	radar,	laser,	GPS,	7	Pentium	computers
Automating automobiles into autonomous automata!
*A.I. lab was established by McCarthy et al. in the early 60s
H2O.ai

Machine Intelligence 18
Step	3:	Big	Data	+	In-Memory	Clusters
2011: Jeopardy (IBM Watson)
In-Memory	Analytics/ML	
4	TB	of	data	(incl.	wikipedia),	90	servers,

16	TB	RAM,	Hadoop,	6	million	logic	rules
Automating question answering and information retrieval!
https://www.youtube.com/watch?v=P18EdAKuC1U https://en.wikipedia.org/wiki/Watson_(computer)
Note: IBM Watson received the question in electronic written form, and was often
able to (electronically) press the answer button faster than the competing humans.
H2O.ai

Machine Intelligence 19
Step	4:	Deep	Learning
2014: Atari Games (DeepMind)
2016: AlphaGo (Google DeepMind)
Deep	Learning

+	reinforcement	learning,	tree	search,

Monte	Carlo,	GPUs,	playing	against	itself,	…
https://deepmind.com
Deep Learning + Smart Algorithms = Master Gamer
Go board has approx.
200,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,
000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000 (2E170) possible positions.
trained	from	raw	pixel	values,	no	human	rules
H2O.ai

Machine Intelligence 20
Step	5:	Improve	Training	Efficiency
2015: MIT, NYU, Toronto
Bayesian	Program	Learning	
(NOT	Deep	Learning)
New algorithm learns handwriting of unseen symbols from
very few training examples (unlike typical Deep Learning)
http://www.nytimes.com/2015/12/11/science/an-advance-in-artificial-
intelligence-rivals-human-vision-abilities.html
H2O.ai

Machine Intelligence 21
Microsoft	A.I.	goes	rogue
https://twitter.com/
TayandYou/with_replies
P.S. Microsoft won the Visual Recognition challenge:
http://image-net.org/challenges/LSVRC/2015/
H2O.ai

Machine Intelligence 22
What	ELSE	can	Deep	Learning	do?
http://www.cs.toronto.edu/~graves/handwriting.cgi
Deep Learning can generate handwriting
H2O.ai

Machine Intelligence 23
What	ELSE	can	Deep	Learning	do?
http://karpathy.github.io/2015/05/21/rnn-effectiveness/
Image captioning:
“black and white dog
jumps over bar.”
Deep Learning can generate code, captions, language, etc.
DL twitter bot
Generated (bogus) math proof:
H2O.ai

Machine Intelligence 24
http://techcrunch.com/2015/01/14/amaaaaaazing/
Quest Visual (acquired by Google)
What	ELSE	can	Deep	Learning	do?
Deep Learning can translate any language
H2O.ai

Machine Intelligence 25
What	ELSE	can	Deep	Learning	do?
Deep Learning can create masterpieces: Semantic Style Transfer
https://github.com/alexjc/neural-doodle
H2O.ai

Machine Intelligence 26
State	of	AI	today
Today’s A.I. can simulate human behavior, but

only for the tasks it was programmed for.
It’s just very good at some board games. And at driving
cars. And at speaking any language. And at handwriting.
And at much more, but it doesn’t (yet) generalize to
arbitrary capabilities.
It doesn’t care to vote for the next president.
It doesn’t care about the NBA playoffs.
It doesn’t decide to take a day off to go play golf.
H2O.ai

Machine Intelligence 27
What	next?
Anything that can be automated will be automated.
Jobs of the past:
assembly line work, teller (ATMs), taxi-firm receptionist
Jobs being automated away now:
resume matching, driving, language translation, education
Jobs being automated away soon:
healthcare, arts & crafts, entertainment, design, decoration,
software engineering, politics, management, professional
gaming, financial planning, auditing, real estate agent
Jobs of the future:
professional sports, food & wine reviewer
H2O.ai

Machine Intelligence 28
Maybe	we’ll	finally	get	the	eating	machine?
https://www.youtube.com/watch?v=n_1apYo6-Ow
1936 Modern Times (Charlie Chaplin)
H2O.ai

Machine Intelligence 29
What	will	change?
Jerry Kaplan, Stanford
http://research.microsoft.com/apps/video/default.aspx?id=258318
Future
headlines
“In a few decades a cheap computer may compute as much
as all human brains combined — and everything is going to
change; every aspect of civilization is going to be affected
and transformed by that.”
- Jürgen Schmidhuber (Deep Learning pioneer)
http://www.ibtimes.co.uk/what-are-ai-neural-networks-how-are-they-applied-financial-markets-1545896
H2O.ai

Machine Intelligence 30
Technology	has	always	created	jobs
U.S. workforce in agriculture
1800: 90%
2000: <2%
A.I. in software:
Today: 1% of all software apps use A.I.
2018: 50% of developers will use A.I. in their software (IDC)
“Intelligent software applications will become commonplace.
And machine learning will touch every industry.”
— Jeff Dean, Google Brain
http://www.nytimes.com/2016/03/26/technology/the-race-is-
on-to-control-artificial-intelligence-and-techs-future.html
H2O.ai

Machine Intelligence 31
H2O.ai	-	Makers	of	H2O
H2O	-	Open-Source	Software	
• 100%	Apache	2.0	open	source	(github.com/h2oai)	
• Scalable	Data	Science	Platform	(AI	Engine	for	Business	Transformation)	
• Distributed	Columnar	Data	Frame	and	Map/Reduce	Backend	
• Deep	Learning,	Gradient	Boosting,	Random	Forest,	Generalized	Linear	
Modeling,	K-Means,	PCA,	GLRM,	…		
Easy	to	Train	and	Operationalize	Models	
• h2o.ai/download	and	run	anywhere,	immediately	
• R,	Python,	Java,	Scala,	REST,	GUI	client	APIs	
• Spark	(cf.	Sparkling	Water),	Hadoop,	Standalone	
• Auto-generated	Java	scoring	code	
• Vibrant	user	community
H2O.ai

Machine Intelligence
	Client	APIs:	R,	Python,	Java,	Scala,	Flow
32
library(h2o)	
h2o.init()	
h2o.deeplearning(x=1:4,y=5,as.h2o(iris))
import	h2o	
from	h2o.estimators.deeplearning	import	H2ODeepLearningEstimator	
h2o.init()	
dl	=	H2ODeepLearningEstimator()	
dl.train(x=list(range(1,4)),	y="Species",	training_frame=iris.hex)
import	_root_.hex.deeplearning.DeepLearning	
import	_root_.hex.deeplearning.DeepLearningParameters	
val	dlParams	=	new	DeepLearningParameters()	
dlParams._train	=	iris.hex	
dlParams._response_column	=	‘Species	
val	dl	=	new	DeepLearning(dlParams)	
val	dlModel	=	dl.trainModel.get
All	heavy	lifting	is	done	by	the	backend!
Built-in	
web	GUI	
and	
Notebook
H2O.ai

Machine Intelligence 33
Gradient Boosting Tree Model
Auto-generated

Java scoring code
to
Operationalize Data Science
Easily	Bring	Models	into	Production
READ MORE
H2O.ai

Machine Intelligence 34
Live	H2O	Deep	Learning	Demo:	Predict	Airplane	Delays
10 nodes:

all 320 cores busy
real-time, interactive
model inspection in Flow
116M rows, 6GB CSV file

800+ predictors (numeric + categorical)
fast training in <1 min:

2M+ samples/second
4 hidden layers
H2O.ai

Machine Intelligence
Selected (customer) use cases…
35
H2O.ai

Machine Intelligence
User	Based	Insurance
WATCH NOW
WATCH NOW
“H2O is an enabler in how people
are thinking about data.”
“We have many plans to use H2O
across the different business units.”
36
H2O.ai

Machine Intelligence
Digital	Marketing	-	Campaigns
“H2O gave us the capability to do Big
Modeling. There is no limit to scaling in H2O.”
“Working with the H2O
team has been amazing.”
“The business value that we have gained
from advanced analytics is enormous.”
WATCH NOW
WATCH NOW
37
H2O.ai

Machine Intelligence
WATCH NOW
WATCH NOW
Matching	TV	Watching	Behavior	with	Buying	Behavior
“Unlike other systems where I had
to buy the whole package and just
use 10-20%, I can customize H2O
to suit my needs.”
“I am a big fan of open source. H2O is
the best fit in terms of cost as well as ease
of use and scalability and usability.”
38
H2O.ai

Machine Intelligence
WATCH NOW
WATCH NOW
Insurance	-	Risk	Assessment
“Predictive analytics is the differentiator
for insurance companies going forward
in the next couple of decades.”
“Advanced analytics was one of the
key investments that we decided to
make.”
39
H2O.ai

Machine Intelligence
Fintech	-	Fraud/Risk/Churn/etc.
“H2O is a great solution because it's
designed to be enterprise ready and
can operate on very large datasets.”
”H2O has been a one-stop shop that helps
us do all our modeling in one framework.”
”H2O is the best solution to be able to
iterate very quickly on large datasets
and produce meaningful models.”
WATCH NOW
WATCH NOW
40
H2O.ai

Machine Intelligence 41
H2O	Deep	Learning	Community	Quotes
READ MORE
Kaggle challenge
2nd place winner

Colin Priest
READ MORE
“For	my	final	competition	submission	I	used	an	ensemble	of	
models,	including	3	deep	learning	models	built	with	R	and	h2o.”
“I	did	really	like	H2O’s	deep	learning	implementation	in	
R,	though	-	the	interface	was	great,	the	back	end	
extremely	easy	to	understand,	and	it	was	scalable	and	
flexible.	Definitely	a	tool	I’ll	be	going	back	to.”
H2O.ai

Machine Intelligence 42
READ MORE WATCH NOW
“H2O	Deep	Learning	models	outperform	other	Gleason	
predicting	models.”
READ MORE
“…	combine	ADAM	and	Apache	Spark	with	H2O’s	deep	learning	capabilities	to	predict	
an	individual’s	population	group	based	on	his	or	her	genomic	data.	Our	results	
demonstrate	that	we	can	predict	these	very	well,	with	more	than	99%	accuracy.”
H2O	Deep	Learning	Community	Quotes
H2O.ai

Machine Intelligence 43
Top	13	Tips	&	Tricks	for	H2O	Deep	Learning
Know	your	Math
Use	Early	Stopping
Use	Checkpointing
Use	Regularization
Use	N-fold	Cross-Validation
Perform	HyperParameter	Search
Know	your	Data	(Sparsity/Categoricals)
Tune	Communication	on	Multi-Node
Establish	Baseline	on	Holdout	DataUnderstand	Model	Complexity
Control	Scoring	Overhead
Do	Ensembling
Inspect	Models	in	Flow
READ MORE WATCH NOW
H2O.ai

Machine Intelligence 44
GBM	Tuning	Tutorial	for	R/Python/Flow
Model tuning is the ‘fun part’ of Data Science!
https://github.com/h2oai/h2o-3/blob/master/h2o-docs/src/product/tutorials/gbm/
H2O.ai

Machine Intelligence 45
H2O	Booklets
DOWNLOAD
Get your booklets!
R Python Deep Learning GLMGBMSparkling Water
H2O.ai

Machine Intelligence 46
KDNuggets	Poll	about	Deep	Learning	Tools	&	Platforms
http://www.kdnuggets.com
H2O	and	TensorFlow	are	tied
H2O.ai

Machine Intelligence 47
TensorFlow	+	H2O	+	Apache	Spark	=	Anything	is	possible
https://github.com/h2oai/sparkling-
water/blob/master/py/examples/
notebooks/TensorFlowDeepLearning.ipynb
https://www.youtube.com/watch?v=62TFK641gG8
In	development:	TensorFlow/GPU	integration	(incl.	ConvNets/RNNs)
H2O.ai

Machine Intelligence 48
Steam	-	Automated	Platform	to	Build	and	Scale	Smart	Data	Products
DevOps/Data	Engineers
Data	Scientists
Advanced	Data	Scientists
Software	Engineers
Application	Software	Engineers
DATA
BUSINESS	
INSIGHTS
AI	–	Machine	Learning Automation Scalability Visualization
In	Development
H2O.ai

Machine Intelligence 49
H2O OPEN TOUR 

w w w. O P E N . H 2 O . A I
We’re	coming	to	a	town	near	you	in	NYC	/	TX
H2O.ai

Machine Intelligence
A.I. and Deep Learning are hot (again)!
Keep up and make your own

smart data products with H2O!
50
h2o.ai/download
https://www.youtube.com/user/0xdata/videos
https://github.com/h2oai/h2o-3
H2O Google Group
@h2oai
Summary
We’re hiring: h2o.ai/careers/

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