create machine learning (ml) models in minutes using automl

Ruchita Arora, Principal Product Manager, Amazon SageMaker

May 27, 2021

Create Machine Learning (ML) Models in Minutes Using AutoMLAmazon SageMaker Autopilot

Agenda

What is AutoML?Amazon SageMaker AutopilotDeep diveDemoCustomer Success

What is AutoML?

Removes the tedious, iterative, and time-consuming work across the ML workflow From data acquisition to model operationalization Preparing data, engineering features, training and tuning models, deploying models, and ongoing model monitoring and updating

What is AutoML?

You spend less time on low level details and more time on using ML to improve business outcomes.

Helping accelerate Machine Learning

AWS AutoML offerings

AutoML is embedded into virtually all AWS ML services, simplifying the integration of ML within your business

Simplified ML

Whether you’re a business user, data scientist, or developer, AWS has AutoMLsolutions for you

ML for all practitioners

AWS makes it easy to dive deep into the models generated by AutoML

Full transparency

You can apply ML at scale using the 70+ end-to-end solutions

End-to-end solutions

Learn more about AutoML from AWS: https://aws.amazon.com/machine-learning/automl/

AWS AutoML offerings

AWS AutoML offeringsAutoML with Amazon SageMaker

Amazon SageMaker Studio

Collaboration at scale

Share notebooks without tracking

code dependencies

Easy experiment

managementOrganize, track, and compare thousands

of experiments

Automatic model

generationGet accurate models with full visibility and

control without writing code

Higher quality ML models

Automatically debug errors, monitor models,

and maintain high quality

Increased productivityCode, build, train,

deploy, and monitor in a unified

visual interface

Fully Integrated Development Environment (IDE) for machine learning

Amazon SageMaker Autopilot

Amazon SageMaker Autopilot automatically builds, trains, and tunes the best machine learning models

based on your data, while allowing you to maintain full control and visibility.

Automatically create machine learning models with full visibility

Bring Data Run SageMakerAutopilot

Deploy Model Make Predictions

101011010010101010000011110

Manually create machine learning models

Data Preparation and Feature Engineering

Model Tuning Model DeploymentModel Training

1 3 42

Automate with Amazon SageMaker Autopilot

Data Preparation and Feature Engineering

Model Tuning Model DeploymentModel Training

1 3 42

What kind of problems can Amazon SageMaker Autopilot handle?• Works with tabular

datasets• Regression: Predict a

continuous value for a new input

• Classification: Place an observation into one of two (binary) or one of multiple (multi) classes or kinds

• Use cases such as:o Customer churn

predictiono Customer lifetime valueo Price predictiono Rick assessmento Sale predictiono Loan risk classification

How Amazon SageMaker Autopilot works

Data Exploration and Preprocessing

Dataset Exploration Notebook:• Dataset statistics: row-

wise and column-wise• Suggested remedies for

common data set problems

Model Training results

Explainability with Feature importance:• Understand and explain

how models created with SageMaker Autopilot make predictions

• Identify how each attribute in your training data contributes to the predicted result as a percentage

Using Amazon SageMaker Autopilot for Model Candidates

Fully runnable model candidate notebook:• Data transformers• Featurization techniques

applied• Override points:

• Algorithms considered• Evaluation metric• Hyper-parameter ranges• Model search strategy• Instances used

Automatic model creation for tabular data with full visibility & control

Provide your data in a tabular form &

specify target prediction

Generate ML models with feature

engineering & model tuning automatically

Get notebooks for your models with

source code

Get a leaderboard & continue to improve your

Complete integration with Amazon SageMakersecurity and compliance features

Use IAM Policies to control access to data, models, and

endpoints

CloudWatch and CloudTrail

integrationSupport

Support for PrivateLink VPC

endpoints, encryption at rest

and in-transit

SOC, PCI, FedRAMP, HIPAA, and more

Customer Success – Freddy’s

Freddy’s grows revenue, sees double-digit comp sales growth using Domo, powered by Amazon SageMaker Autopilot, and optimizes pricing

and menu mix

Customer Success – HawkEye 360

HawkEye 360 uses Amazon SageMaker Autopilot to rapidly generate high-quality AI models for maritime vessel risk assessment

Skullcandy identifies key themes, products, and friction points impacting customer satisfaction scores using Sisense, powered by

Customer Success – Skullcandy

Learn MoreAmazon SageMaker Autopilot –https://aws.amazon.com/sagemaker/autopilot/

User Guide and APIhttps://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.htmlhttps://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-reference.html

AWS AutoML Solutions -https://aws.amazon.com/machine-learning/automl/

AWS Machine Learning Summit -https://aws.amazon.com/events/summits/machine-learning/

Thank you!

create machine learning (ml) models in minutes using automl

Documents

ml-1640, ml-2240, ml-2241, ml-2245 general

oboe: collaborative filtering for automl...

results of the automl challenge -...

· construccion de la area materno e infantil del centro...

the importance of automl€¦ · influence the structure of...

ml 320 ml 350 ml 500 ml 55 amg

coloration de perls...hcl 1n = 10ml, eau distillée = 40 ml,...

workshop deep learning: ai applications and trends · deep...

automl-zero: evolving machine learning …automl-zero:...

sin título-1 › media › k2 › attachments ›...

ml princess, ml solo, ml flex air humidification

extrapolating learning curves of deep neural...

final - english · english breakfast 20 camomile 20 earl...

building and benchmarking automl systems · • automatic...

automatic machine learning, automl

grey-box optimization for automl (& more)grey-box...

machine intelligence at google scale - api conference ·...

evolutionary neural automl for deep learningevolutionary...

oboe: collaborative filtering for automl initializationoboe:...

standard operating procedures - clu-in to 400ec for 30...