More Related Content Similar to How to train and deploy your machine learning models with Amazon SageMaker (20) More from Amazon Web Services (20) How to train and deploy your machine learning models with Amazon SageMaker1. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark.
Kwunhok Chan
Solutions Architect, AWS
How to Train and Deploy your Machine Learning
Models with Amazon SageMaker
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The AWS ML Stack
Broadest and most complete set of Machine Learning capabilities
VISION SPEECH TEXT SEARCH CHATBOTS PERSONALIZATION FORECASTING FRAUD DEVELOPMENT CONTACT CENTERS
Ground
Truth
AWS
Marketplace
for ML
Neo Augmented
AIBuilt-in
algorithms
Notebooks Experiments Processing
Model
training &
tuning
Debugger Autopilot
Model
hosting
Model Monitor
Deep Learning
AMIs & Containers
GPUs & CPUs
Elastic
Inference
Inferentia FPGA
Amazon
Rekognition
Amazon
Polly
Amazon
Transcribe
+Medical
Amazon
Comprehend
+Medical
Amazon
Translate
Amazon
Lex
Amazon
Personalize
Amazon
Forecast
Amazon
Fraud Detector
Amazon
CodeGuru
AI SERVICES
ML SERVICES
ML FRAMEWORKS & INFRASTRUCTURE
Amazon
Textract
Amazon
Kendra
Contact Lens
For Amazon Connect
SageMaker Studio IDE
Amazon SageMaker
DeepGraphLibrary
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The machine learning workflow is iterative and complex
Prepare Build Train & Tune Deploy & Manage
101011010
010101010
000011110
Collect and
prepare
training data
Choose or build an
ML algorithm
Set up and manage
environments
for training
Train, debug, and
tune models
Deploy
model in
production
Manage training runs Monitor
models
7. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark.
Fully managed data
processing jobs and
data labeling
workflows
One-click collaborative
notebooks and built-
in, high performance
algorithms and models
One-click
training
Debugging and
optimization
One-click
deployment and
autoscaling
Amazon SageMaker helps you build, train, and deploy models
Visually track and
compare experiments
Automatically
spot
concept drift
Fully
managed with
auto-scaling
for 75% less
Prepare Build Train & Tune Deploy & Manage
101011010
010101010
000011110
Collect and
prepare
training data
Choose or bring
your own
ML algorithm
Set up and manage
environments
for training
Train, debug, and
tune models
Deploy
model in
production
Manage training runs Monitor
models
Add human
review of
predictions
Web-based IDE for machine learning
Automatically build and train models
8. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark.
Fully managed data
processing jobs and
data labeling
workflows
One-click collaborative
notebooks and built-
in, high performance
algorithms and models
One-click
training
Debugging and
optimization
One-click
deployment and
autoscaling
Amazon SageMaker helps you build, train, and deploy models
Visually track and
compare experiments
Automatically
spot
concept drift
Fully
managed with
auto-scaling
for 75% less
Prepare Build Train & Tune Deploy & Manage
101011010
010101010
000011110
Collect and
prepare
training data
Choose or bring
your own
ML algorithm
Set up and manage
environments
for training
Train, debug, and
tune models
Deploy
model in
production
Manage training runs Monitor
models
Add human
review of
predictions
Web-based IDE for machine learning
Automatically build and train models
9. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark.
• Reduce data labeling costs by up to 70%
• Access labelers through Amazon Mechanical Turk, Amazon
approved vendors, or use private human labelers
• Achieve accurate results quickly
Build highly accurate training datasets using
machine learning
Amazon SageMaker Ground Truth
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Successful models require high-quality data
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How Amazon SageMaker Ground Truth Works
Automatic
annotations
Raw data Human
annotations
Training data
Human
annotations
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Demo
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Fully managed data
processing jobs and
data labeling
workflows
One-click collaborative
notebooks and built-
in, high performance
algorithms and models
One-click
training
Debugging and
optimization
One-click
deployment and
autoscaling
Amazon SageMaker helps you build, train, and deploy models
Visually track and
compare experiments
Automatically
spot
concept drift
Fully
managed with
auto-scaling
for 75% less
Prepare Build Train & Tune Deploy & Manage
101011010
010101010
000011110
Collect and
prepare
training data
Choose or bring
your own
ML algorithm
Set up and manage
environments
for training
Train, debug, and
tune models
Deploy
model in
production
Manage training runs Monitor
models
Add human
review of
predictions
Web-based IDE for machine learning
Automatically build and train models
14. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark.
Fully integrated development environment (IDE) for machine learning
Amazon SageMaker Studio (Preview)
Organize, track, and
compare thousands of
experiments
Share notebooks
without tracking code
dependencies
Get accurate models with
full visibility & control
without writing code
Automatically debug errors,
monitor models, & maintain
high quality
Code, build, train, deploy, &
monitor in a unified visual
interface
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Demo
16. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark.
Get started with Amazon SageMaker
Amazon SageMaker Studio
Integrated Development environment(IDE) for Machine Learning
Amazon SageMaker Autopilot
Automatically build and train models
Amazon SageMaker Model Monitor
Automatically detect concept drift
Amazon SageMaker Notebooks
One-click notebooks with elastic compute
Amazon SageMaker Experiments
Capture, organize, and compare every step
Amazon SageMaker Neo
Train once, deploy anywhere
AWS Marketplace
Pre-built algorithms, models, and data
Amazon SageMaker Debugger
Debug and profile training runs
Automatic Model Tuning
One-click hyperparameter optimization
Amazon Augmented AI
Add human review of model predictions
Amazon SageMaker GroundTruth
Build and manage training dataset
Prepare Build Train & Tune Deploy & Manage
Processing Job
Supports Python or Spark
One Click Training
Supports supervised, unsupervised & RL
One Click Deployment
Supports real-time, batch & multi-model
Amazon Elastic Inference
Auto scaling for 75% less
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Resources
Amazon SageMaker Webpage
https://aws.amazon.com/sagemaker
Developer Resources
https://aws.amazon.com/sagemaker/developer-resources/
Sample Notebooks
https://github.com/awslabs/amazon-sagemaker-examples
SageMaker Workshop
https://sagemaker-workshop.com/
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is Now Open
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Kong Region Website
Register to the
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