A DEVELOPER’S INTRODUCTION TO AZURE MACHINE LEARNING

JOHN GARLANDPRINCIPAL CONSULTANT & INSTRUCTORWINTELLECT@DOTNETGATOR

@ATLCODECAMPHTTPS://ATLANTACODECAMP.COM/2016

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ABOUT ME•Principal Consultant & Instructor at

ConsultingCustom software application development & architectureInstructor Led TrainingMicrosoft’s #1 training vendor in DevDivOn-Demand TrainingWorld class, subscription-based online training

• Author•Windows Store Apps Succinctly• Programming the Windows Runtime by Example

•Microsoft Azure MVP & Advisor

WHAT IS MACHINE LEARNING?• Using computer power to gain insight into

data that might otherwise be elusive• Credit-card fraud detection• Online shopping recommendations• Self-driving cars and more

• “Turning data into software”• Machine Learning Strategies• Supervised learning• Unsupervised learning

TRADITIONAL PROGRAMMING VS MACHINE LEARNING

Program Data Output Data Output Progra

m

Traditional Programming

Machine Learning

MACHINE LEARNING PROCESS

PrepareData

• Import data• Pre-process data

TrainModel

• Select Learning Algorithm & Build Model• Experiment/Iterate/Evaluate

MakeOperationa

l

• Prepare model for deployment• Deploy & call from applications

AZURE MACHINE LEARNING

• Fully managed cloud service for building and operationalizing ML models

Fully ManagedNo software to install, no hardware to manage, and one portal to view and update.

Integrated

Simple drag, drop, and connect interface. No need for programming for common tasks.

Best in Class Algorithms + RBuilt-in collection of best of breed algorithms. Support for R and popular CRAN packages.

Deploy in MinutesOperationalize models with a single click. Monetize in Machine Learning Marketplace.

AZURE MACHINE LEARNING HISTORY

AZURE MACHINE LEARNING STUDIO•https://studio.azureml.net•Online IDE to build, test, and deploy machine learning models•Drag and drop “modules”

Demo

PRICINGFree Tier Standard Tier

Azure Subscription

Not Required Required

Max Modules 100 Per Experiment UnlimitedMax Duration 1 Hour Per Experiment 7 Days Per Experiment, 24 Hours Per

ModuleMax Storage 10GB BYO (Azure Blob)Performance Single node Multiple nodesSLA No Yes

$9.99/Seat/Month$1/Studio Experiment Hour$2/Production API Compute Hour$.50/1,000 Production API Transactions

OTHER RESOURCES

Free e-book

http://bit.ly/a4r-mlebook

Not free book

http://bit.ly/pa-mlbook

http://bit.ly/Build2016Videos

Surveys and Prizes Please complete the session and event surveys!1 ticket per session survey1 ticket for the event survey1 ticket for completing the booth game

Drawing for prizes begins at 5pm in Q202

THANK YOU!

John GarlandPrincipal Consultant & InstructorWintellect@dotnetgator

A link to these slides will be posted on Twitter with a reference to @ATLCodeCamp