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H2O Machine Learning and Kalman Filters for Machine Learning Hank Roark @hankroark [email protected]

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Page 1: H2O Machine Learning and Kalman Filters for Machine Prognostics

H2OMachine Learning andKalman Fi lters for Machine Learning

HankRoark@[email protected]

Page 2: H2O Machine Learning and Kalman Filters for Machine Prognostics

WHOAMI ILead,[email protected]

JohnDeere:Research,SoftwareProductDevelopment, HighTechVenturesLotsoftimedealingwithdataoffofmachines,equipment, satellites, weather,radar,handsampled, andon.Geospatial, temporal/timeseries dataalmostall fromsensors.Previouslyatstartupsandconsulting (RedSkyInteractive,Nuforia,NetExplorer, PerotSystems,afewofmyown)

Engineering&ManagementMITPhysicsGeorgiaTech

[email protected]@hankroarkhttps://www.linkedin.com/in/hankroark

Page 3: H2O Machine Learning and Kalman Filters for Machine Prognostics

IF YOUARE INTO DATA, THE IOTHAS IT

Page 4: H2O Machine Learning and Kalman Filters for Machine Prognostics

WHYTHIS EXAMPLE?

GETREADY FORBRONTOBYTES!!

Page 5: H2O Machine Learning and Kalman Filters for Machine Prognostics

WOW,HOWBIG ISABRONTOBYTE?

Page 6: H2O Machine Learning and Kalman Filters for Machine Prognostics

Image courtesy http://www.telecom-cloud.net/wp-content/uploads/2015/05/Screen-Shot-2015-05-27-at-3.51.47-PM.png

This much data wil l requirea fastOODA loop

Page 7: H2O Machine Learning and Kalman Filters for Machine Prognostics

EXAMPLE FROMTHE IOTDomain:PrognosticsandHealthManagementMachine:TurbofanJetEnginesDataSet:A.Saxena andK.Goebel(2008)."TurbofanEngineDegradationSimulationDataSet",NASAAmesPrognosticsDataRepository

PredictRemainingUseful LifefromPartialLifeRuns

Sixoperatingmodes,twofailuremodes,manufacturingvariability

Training:249jetengines runtofailureTest: 248jetengines

Page 8: H2O Machine Learning and Kalman Filters for Machine Prognostics

LOADING DATA

Page 9: H2O Machine Learning and Kalman Filters for Machine Prognostics

PYTHON (ANDR) OBJECTS ARE PROXIES FOR BIGDATA

STEP 1

Python user

h2o_df = h2o.import_file(“hdfs://path/to/data.csv”)

Page 10: H2O Machine Learning and Kalman Filters for Machine Prognostics

H2O

H2O

H2O

data.csv

HTTP REST API request to H2Ohas HDFS path

H2O ClusterInitiate distributed ingest

HDFSNFSS3

Request data from HDFS

STEP 2

2.2

2.3

2.4

Python

h2o.import_file()

2.1Python function

call

PYTHON(ANDR ) OB JECTSARE PROXIES FOR B IG DATA

Page 11: H2O Machine Learning and Kalman Filters for Machine Prognostics

H2O

H2O

H2O

Python

HDFSNFSS3

STEP 3

Cluster IPCluster Port

Pointer to Data

Return pointer to data in REST API JSON

Response

HDFS provides data

3.3

3.43.1h2o_df object created

in Python

data.csv

h2o_dfH2O

Frame

3.2Distributed H2OFrame in DKV

H2O Cluster

PYTHON(ANDR ) OB JECTSARE PROXIES FOR B IG DATA

Page 12: H2O Machine Learning and Kalman Filters for Machine Prognostics

SUMMARY STATISTICS

Page 13: H2O Machine Learning and Kalman Filters for Machine Prognostics

CREATETHETARGETVARIABLE

Calculate TotalCyclesForEachUnit

Page 14: H2O Machine Learning and Kalman Filters for Machine Prognostics

CREATETHETARGETVARIABLE

AppendToOriginalFrame

Page 15: H2O Machine Learning and Kalman Filters for Machine Prognostics

CREATETHETARGETVARIABLE

CreateNewFeatureofCycles

Remaining

Page 16: H2O Machine Learning and Kalman Filters for Machine Prognostics

EXPLORATORY DATA ANALYSISBooleanIndexing

Page 17: H2O Machine Learning and Kalman Filters for Machine Prognostics

EXPLORATORY DATA ANALYSISSamplethedatatolocalmemory

Page 18: H2O Machine Learning and Kalman Filters for Machine Prognostics

EXPLORATORY DATA ANALYSIS

Useyourfavorite

visualizationtools

(Seaborn!)

Ugh,wherearetrends

overtimeTime

ZeroRemainingUsefulLife

Page 19: H2O Machine Learning and Kalman Filters for Machine Prognostics

MODEL BASEDDATAENRICHMENTSensor

measurementsappearinclusters

Correspondingtooperating

mode!

Page 20: H2O Machine Learning and Kalman Filters for Machine Prognostics

FEATUREENGINEERING

UseH2Ok-meanstofindcluster

centers

Page 21: H2O Machine Learning and Kalman Filters for Machine Prognostics

FEATUREENGINEERING

Enrichexisting datawithoperatingmode

membership

Page 22: H2O Machine Learning and Kalman Filters for Machine Prognostics

MOREFEATUREENGINEERINGFornon-constant

sensormeasurements

withinanoperatingmode,

Standardizeeachsensormeasurementbyoperatingmode

Basedonthetrainingdata

Page 23: H2O Machine Learning and Kalman Filters for Machine Prognostics

TRENDSOVER TIME!

BeforeH2ODataPreparation

ReadyforH2OLearning

Time Time

Page 24: H2O Machine Learning and Kalman Filters for Machine Prognostics

MODELING - SIMPLE

ConfigureanEstimator

Page 25: H2O Machine Learning and Kalman Filters for Machine Prognostics

MODELING - SIMPLE

Train anEstimator

Page 26: H2O Machine Learning and Kalman Filters for Machine Prognostics

PYTHONSCRIPTSTARTING H2OGLM

HTTP

REST/JSON

POST/3/ModelBuilders/glm

glm_estimator.train()

Pythonscript

StandardPythonprocess

TCP/IP

HTTP

REST/JSON

/3/ModelBuilders/glm endpoint

Job

GLMalgorithm

GLMtasks

Fork/Joinframework

K/Vstoreframework

H2Oprocess

Networklayer

RESTlayer

H2O- algos

H2O- core

Userprocess

H2Oprocess

Legend

Page 27: H2O Machine Learning and Kalman Filters for Machine Prognostics

HTTP

REST/JSON

GET /3/Models/model_id

glm_estimator.show()

Pythonscript

StandardPythonprocess

TCP/IP

HTTP

REST/JSON

/3/Modelsendpoint

Fork/Joinframework

K/Vstoreframework

H2Oprocess

Networklayer

RESTlayer

H2O- algos

H2O- core

Userprocess

H2Oprocess

Legend

PYTHON SCRIPT STARTING H2OGLM

Page 28: H2O Machine Learning and Kalman Filters for Machine Prognostics

MODEL EVALUATIONEvaluate Performance

ataglanceinPython

Page 29: H2O Machine Learning and Kalman Filters for Machine Prognostics

MODEL EVALUATIONEvaluate Performance

ataglanceinH2OFlow

Page 30: H2O Machine Learning and Kalman Filters for Machine Prognostics

MODEL EVALUATIONEvaluate Performance

ataglancegraphically inPython

Page 31: H2O Machine Learning and Kalman Filters for Machine Prognostics

CROSS VALIDATION

SetupHyperparameterSearchOptions

Page 32: H2O Machine Learning and Kalman Filters for Machine Prognostics

CROSS VALIDATION

Configurefullfull

gridsearch

Page 33: H2O Machine Learning and Kalman Filters for Machine Prognostics

CROSS VALIDATION

Executegridsearch

Page 34: H2O Machine Learning and Kalman Filters for Machine Prognostics

CROSS VALIDATION

Evaluate results&modelselection

Page 35: H2O Machine Learning and Kalman Filters for Machine Prognostics

OPEN– SCIKITPIPELINES

Create Pipelines

Hyper-parameter Options

Crossvalidationstrategy

Hyper-parameterSearchStrategy

Fit

Page 36: H2O Machine Learning and Kalman Filters for Machine Prognostics

KALMAN - POSTPROCESSING

Page 37: H2O Machine Learning and Kalman Filters for Machine Prognostics

RESOURCES

• Downloadandgo:http://www.h2o.ai/download• Documentation:http://docs.h2o.ai/• Booklets,Datasheet:http://www.h2o.ai/resources/• Github:http://github.com/h2oai/• Training:http://learn.h2o.ai/• ThispresentationandassociatedJupyter notebook

(lookin2016_01_21_MachineLearningAndKalmanFiltersForMachineHealth):https://github.com/h2oai/h2o-meetups/

Page 38: H2O Machine Learning and Kalman Filters for Machine Prognostics

THANK YOU


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