Amazon SageMaker

1. Amazon SageMaker

2. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Platform
Services
AWS ML Stack
Deploy machine learning models with high-performance machine learning
algorithms, broad framework support, and one-click training, tuning, and
inference.

3. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Data Visualization &
Analysis
Business Problem –
ML problem framing Data Collection
Data Integration
Data Preparation &
Cleaning
Feature Engineering
Model Training &
Parameter Tuning
Model Evaluation
Are Business
Goals met?
Model Deployment
Monitoring &
Debugging
YesNo
DataAugmentation
Feature
Augmentation
The Machine Learning Process
Re-training
Predictions

4. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Data Visualization &
Analysis
Business Problem –
ML problem framing Data Collection
Data Integration
Data Preparation &
Cleaning
Feature Engineering
Model Training &
Parameter Tuning
Model Evaluation
Are Business
Goals met?
Model Deployment
Monitoring &
Debugging
YesNo
DataAugmentation
Feature
Augmentation
Problem discovery
Re-training
• Help formulate the right
questions
• Domain Knowledge
Predictions

5. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Data Visualization &
Analysis
Business Problem –
ML problem framing Data Collection
Data Integration
Data Preparation &
Cleaning
Feature Engineering
Model Training &
Parameter Tuning
Model Evaluation
Are Business
Goals met?
Model Deployment
Monitoring &
Debugging
YesNo
DataAugmentation
Feature
Augmentation
Retraining
• Need a data platform?
• Amazon S3
• AWS Glue
• Amazon Athena
• Amazon EMR
• Amazon Redshift
Spectrum
Integration
Predictions

6. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Data Visualization &
Analysis
Business Problem –
ML problem framing Data Collection
Data Integration
Data Preparation &
Cleaning
Feature Engineering
Model Training &
Parameter Tuning
Model Evaluation
Are Business
Goals met?
Model Deployment
Monitoring &
Debugging
YesNo
DataAugmentation
Feature
Augmentation
Retraining
Model Training
Predictions
• Setup and manage
Notebook Environments
• Setup and manage
Training Clusters
• Write Data Connectors
• Scale ML algorithms to
large datasets
• Distribute ML training
algorithm to multiple
machines
• Secure Model artifacts

7. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Data Visualization &
Analysis
Business Problem –
ML problem framing Data Collection
Data Integration
Data Preparation &
Cleaning
Feature Engineering
Model Training &
Parameter Tuning
Model Evaluation
Are Business
Goals met?
Model Deployment
Monitoring &
Debugging
YesNo
DataAugmentation
Feature
Augmentation
Retraining
Model Deployment
Predictions
• Setup and manage Model
Inference Clusters
• Manage and Scale Model
Inference APIs
• Monitor and Debug Model
Predictions
• Models versioning and
performance tracking
• Automate New Model
version promotion to
production (A/B testing)

8. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
End-to-End
Machine Learning
Platform
Zero setup Flexible Model
Training
Pay by the second
$
Amazon SageMaker
Build, train, and deploy machine learning models at scale

9. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Highly-optimized
machine learning
algorithms
BuildPre-built
notebook
instances
Amazon SageMaker

10. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Highly-optimized
machine learning
algorithms
One-click training
for ML, DL, and
custom algorithms
BuildPre-built
notebook
instances
Easier training with
hyperparameter
optimization
Train
Amazon SageMaker

11. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
One-click training
for ML, DL, and
custom algorithms
Easier training with
hyperparameter
optimization
Highly-optimized
machine learning
algorithms
Deployment
without
engineering effort
Fully-managed
hosting at scale
BuildPre-built
notebook
instances
Deploy
Train
Amazon SageMaker

12. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon ECR
Model Training (on EC2)
Model Hosting (on EC2)
Trainingdata
Modelartifacts
Training code Helper code
Helper codeInference code
GroundTruth
Client application
Inference code
Training code
Inference requestInference response
Inference Endpoint
Amazon SageMaker

13. Digital Globe
http://blog.digitalglobe.com/industry/using-machine-learning-
to-save-money-on-cloud-data-storage/
https://www.youtube.com/watch?v=mkKkSRIxU8M
In the last 18 years DigitalGlobe
has been operating Earth imaging
satellites, they have collected over
100 PB of imagery.
There is a trade-off between how
quickly data can be accessed and
how much it will cost to store.
Working with the ML Lab, Digital
Globe built a predictive model that
will reduce cloud storage costs for
their imagery archive by 50%.

14. Detecting buildings in Vietnam
https://developmentseed.org/blog/2018/01/19/sagemaker-label-maker-case/

15. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Demos
1.Use a built-in algorithm:
fine-tuning a pre-trained image classification model
2.Bring your own training code:
distributed training from scratch with MXNet and Gluon
3.Bring your own pre-trained model:
classifying the Iris data set with a pre-trained TensorFlow model
4.Bring your own container:
classifying the Iris data set with Decisions Trees in scikit-learn

16. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
End-to-End
Machine Learning
Platform
Zero setup Flexible Model
Training
Pay by the second
$
Amazon SageMaker
Build, train, and deploy machine learning models at scale

17. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Resources
https://aws.amazon.com/machine-learning
https://aws.amazon.com/blogs/ai
https://aws.amazon.com/sagemaker
An overview of Amazon SageMaker
https://www.youtube.com/watch?v=ym7NEYEx9x4
https://medium.com/@julsimon

18. Thank you!