Solving the Skills GapA Quick Overview of AutoML

Mark Woolnough, Power and AI Architect, IBM Systems6th March 2019

The Challenges of Enterprise AI Adoption

Time to Insights Slow

Weeks to Months

Lack of AI Talent

~100Data Science

“Grandmasters” in the WorldTime for a data scientist

to build a model

Lack of Trust in AI

Black box models

”US alone faces a shortage of 190,000 people with analytical expertise.”

Data Scientists combine skills across various areas of expertise

• Scripting, SQL,Python, R Scala

• Data Pipelines• Big Data,

Apache Spark

• Mathematical Background• Computational Science

• Business/IndustryExpertise

• Domain Knowledge• Supply Chain• CRM• Financials• Networking

Statistician

ComputerScience

DomainExpert

Unicorn

What is AutoML?

4

Automated machine learning (AutoML) is the process of automating the end-to-end process of applying machine

learning to real-world problems.

Confidential5 Confidential5

AutoML

Features Target

Data Quality andTransformation

ModelingTable

ModelBuilding

ModelData Integration

+

AutoML: Automated Data Science and ML Workflows

Highly Iterative Process

What are the benefits to AutoML?

6

ü Cost Reductions

ü Faster Deployment: Increased revenues and customer satisfaction

ü More models in production, more automation, better employee engagement

Ø Increased productivity for data scientistsØ Democratization of machine learning reduces demand for data scientists

ü Can help with machine learning and AI interpretability (i.e, for regulation bodies)

ü Can help audit the quality and accuracy of existing models

AutoML Vendors – an example

7

H2O.ai is a Recognized Leader in AI and ML2018 Gartner Magic Quadrant

for Data Science andMachine Learning Platforms

Forrester Wave: Notebook-Based Predictive Analytics And Machine

Learning Solutions, Q3 2018

Top 3 Artificial Intelligence (AI) and Machine Learning (ML)

Software Solution

“Technology leadership … with a distinguished vision”

“the quasi-industry standard”

“its vision of creating an AI and ML tool that ultimately aims to allow almost everyone within the business to create their own predictive models”

“H2O.ai’s future is automated machine learning”

“its bright future is in Driverless AI”

21 day free trial for Driverless AI

H2O Driverless AI Delivers “Expert Data Scientist in a Box”

• Award-winning software• Created and supported by world

renowned AI experts from H2O.ai• Empowers companies to accomplish

AI and ML with a single platform

• Performs the function of an expert data scientist and adds more power to both novice and expert teams

• Details and highlights insights and interpretability with easy to understand results and visualizations

Supervised Learning

Age Income Last Month Payment

Payment Default

47 $183,342 Yes False

29 $ 84,823 No True

58 $ 95,853 Yes False

63 $ 43,824 Yes True

Training Data

Age Income Last Month Payment

Payment Default

61 $ 73,679 Yes

73 $ 54,428 No

59 $ 90,453 Yes

43 $ 83,041 Yes

Test Data

What’s the pattern?

Can we create model to guess

‘Default’?

Supervised Learning Techniques

Regression: How much will a customers spend?

Classification: Will a customer make a purchase? Yes or No

X

y

xi

xj

yesno

H2O Driverless AI: How it Works

SQL

Local

Amazon S3

HDFS

X Y

AutomaticScoring Pipeline

Machine learningInterpretability

Deploy Low-latencyScoring to Production

Modelling

Dataset

Model Recipes:• i.i.d. data• Time-series• More on the way

Advanced Feature Engineering Algorithm Model

Tuning+ +

Survival of the Fittest

Automatic Machine Learning

Understand the data shape, outliers, missing values, etc.

Powered by GPU Acceleration

1Drag and drop data 2

Automatic Visualization Use best practice model recipes

and the power of high performance computing to Iterate across thousands of possible models including advanced feature engineering and parameter tuning

3Automatic Machine Learning

Deploy ultra-low latency Python or Java Automatic Scoring Pipelines that include feature transformations and models.

4Automatic Scoring Pipelines

Ingest data from cloud, big data and desktop systems

Google BigQuery

Azure Blog Storage

Snowflake

Model Documentation

12

CONFIDENTIAL

Industry Leading Interpretability for Trust and Compliance

• Interpretability for debugging, not just for regulators

• Get reason codes and model interpretability in plain English

• K-Lime, LOCO, partial dependence and more

CONFIDENTIAL

H2O Walk through…

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Scenario: Use AutoML to build and deploy an AI model that will predict when a customer will default payment.

Materials: IBM AC922, H2O Driverless AI, a labelled training data set with payment history of 25,000 clients and their payment status (true/false) and a test data set to validate.

Output: A trained model pipeline for deployment and human readable report showing how it was built.

CONFIDENTIAL

H2O Walk through…

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The data…

Predict this!

CONFIDENTIAL

H2O Walk through…

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| 177 March 2019