Amazon reInvent 2020 Recap: AI and Machine Learning Video here: https://youtu.be/YSXe02Y5pHM NEW RELEASE! Build, Automate, Manage, and Scale ML Workflows with the NEW Amazon SageMaker Pipelines by Hallie Crosby Weishahn. Description of Talk and Demo AWS recently announced Amazon SageMaker Pipelines (https://aws.amazon.com/sagemaker/pipelines/), the first purpose-built, easy-to-use Continuous Integration and Continuous Delivery (CI/CD) service for machine learning. SageMaker Pipelines has three main components which improve the operational resilience and reproducibility of your workflows: 1) pipelines, 2) model registry, and 3) projects. In this talk and demo, Hallie will walk us through the new Amazon SageMaker Pipelines feature including MLOps support. Date/Time 9-10am US Pacific Time (Third Monday of Every Month) RSVP: https://www.eventbrite.com/e/1-hr-free-workshop-pipelineai-gpu-tpu-spark-ml-tensorflow-ai-kubernetes-kafka-scikit-tickets-45852865154 Meetup: https://www.meetup.com/Data-Science-on-AWS/ Zoom: https://zoom.us/j/690414331 Webinar ID: 690 414 331 Phone: +1 646 558 8656 (US Toll) or +1 408 638 0968 (US Toll) Related Links Meetup: https://meetup.datascienceonaws.com GitHub Repo: https://github.com/data-science-on-aws/ O'Reilly Book: https://datascienceonaws.com YouTube: https://youtube.datascienceonaws.com Slideshare: https://slideshare.datascienceonaws.com Support: https://support.pipeline.ai Monthly Workshop: https://www.eventbrite.com/e/full-day-workshop-kubeflow-gpu-kerastensorflow-20-tf-extended-tfx-kubernetes-pytorch-xgboost-tickets-63362929227 RSVP: https://www.eventbrite.com/e/1-hr-free-workshop-pipelineai-gpu-tpu-spark-ml-tensorflow-ai-kubernetes-kafka-scikit-tickets-45852865154

1. © 2021, Amazon Web Services, Inc. or its affiliates. All rights reserved.
https://www.amazon.com
/dp/1492079391/

2. Data Science on AWS Meetup
Dec 21, 2020

3. © 2021, Amazon Web Services, Inc. or its affiliates. All rights reserved.
VISION SPEECH TEXT SEARCH CHATBOTS PERSONALIZATION FORECASTING FRAUD CONTACT CENTERS
Deep
Learning
AMIs &
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INDUSTRIAL AI CODE AND DEVOPS
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Voice ID
For Amazon Connect
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for Metrics
ANOMALY DETECTION
Amazon
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Medical
Amazon
Comprehend
Medical
Amazon
SageMaker
Label
data
NEW
Aggregate &
prepare data
NEW
Store & share
features
Auto ML Spark/R
NEW
Detect
bias
Visualize in
notebooks
Pick
algorithm
Train
models
Tune
parameters
NEW
Debug &
profile
Deploy in
production
Manage
& monitor
NEW
CI/CD
Human
review
NEW: Model management for edge devices
NEW: SageMaker JumpStart
SAGEMAKER STUDIO IDE

4. © 2021, Amazon Web Services, Inc. or its affiliates. All rights reserved.
VISION SPEECH TEXT SEARCH CHATBOTS PERSONALIZATION FORECASTING FRAUD CONTACT CENTERS
AI SERVICES
Amazon
Rekognition
Amazon
Polly
Amazon
Transcribe
+Medical
Amazon
Lex
Amazon
Personalize
Amazon
Forecast
Amazon
Comprehend
+Medical
Amazon
Textract
Amazon
Kendra
Amazon
CodeGuru
Amazon
Fraud Detector
Amazon
Translate
INDUSTRIAL AI CODE AND DEVOPS
NEW
Amazon
DevOps Guru
Voice ID
For Amazon Connect
Contact Lens
NEW
Amazon
Monitron
NEW
AWS Panorama
+ Appliance
NEW
Amazon Lookout
for Vision
NEW
Amazon Lookout
for Equipment
AI Services: Easily add intelligence to application
NEW
Amazon
HealthLake
HEALTH AI
NEW
Amazon Lookout
for Metrics
ANOMALY DETECTION
Amazon
Transcribe
Medical
Amazon
Comprehend
Medical

5. © 2021, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Amazon
SageMaker
Label
data
Aggregate &
prepare data
Store & share
features
Auto ML Spark/R Detect bias
Visualize in
notebooks
Pick
algorithm
Train
models
Tune
parameters
Debug &
profile
Deploy in
production
Manage
& monitor
CI/CD
Human
review
Ground
Truth
NEW
Data Wrangler
NEW
Feature
store Autopilot Processing
NEW
Clarify
Studio
Notebooks
Built-in or
Bring-your-own
NEW
Experiments
Spot Training
Distributed
Training
Automatic
Model
Tuning
Debugger
NEW
Model Hosting
Multi-model
Endpoints
Model
Monitor
NEW
Pipelines
Augmented
AI
NEW: AMAZON SAGEMAKER EDGE MANAGER
SAGEMAKER STUDIO IDE
AMAZON SAGEMAKER JUMPSTART
ML SERVICES
ML Services: Amazon SageMaker

6. © 2021, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Amazon SageMaker overview

7. 7© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
SageMaker
JumpStart
Easily and quickly
bring machine learning
applications to market
Leverage solutions out-of-the-box or customize for a specific business problem
15+ pre-built solutions for common ML use cases
Use one-click deployable ML models and algorithms from popular model zoos
Accelerate time to deploy over 150 open source models
Easily bring ML applications to market using pre-built solutions, ML models and
algorithms from popular model zoos, and getting started content
Get started with just a few clicks

8. 8© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Amazon SageMaker JumpStart pre-built solutions
Predictive
Maintenance
Predictive
maintenancefor
manufacturing >
Predictive maintenance
for vehicle fleets >
Demand
Forecasting
Demand forecasting
with deep learning >
Fraud
Detection
Detect malicious users
and transactions >
Fraud detection in
financial transactions
using deep graph library >
Credit Risk
Prediction
Explain credit decisions >
Extract & Analyze
Data from Documents
Document summarization,
entity, and relationship
extraction >
Handwriting recognition >
Filling in missing values in
tabular records >
Differential privacy for
sentiment classification >
Computer
Vision
Product defect
detection in images >
Autonomous
Driving
Visual perception with
active learning >
Personalized
Recommendations
Entity resolution in
identity graphs >
Purchase modeling >
Churn
Prediction
Churn prediction with
text >
Learn more about solutions:
https://aws.amazon.com/sagemaker/getting-started/

9. 9© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Amazon SageMaker JumpStart open source models
150+ pre-trained open source models from PyTorch Hub & TensorFlow Hub
TASKS MODELS
VISION
TEXT

10. 10© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Easily launch solutions and deploy or fine-tune models
Launch solutions, or deploy
or fine-tune pre-trained
models with a single click
Easily manage assets from
Amazon SageMaker
JumpStart
Open pre-populated
notebooks for solutions
and inference on deployed
models

11. 11© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
SageMaker
Data Wrangler
The fastest and easiest
way to prepare data for
machine learning
Support for data from multiple sources
Quickly select and query data
Use built-in data transformations to covert raw data to features for machine
learning
Easily transform data with built-in data transformations
Complete flexibility to bring your own custom transformations in in PySpark, SQL,
or Pandas
Customize data transformations
Quickly detect outliers or extreme values – all without writing code
Understand data visually
Diagnose potential issues in data preparation workflows that could hinder ML model
accuracy
Quickly estimate ML model accuracy
Deploy data preparation workflows into production with
a single click
Manage all steps of the data preparation workflow through a single visual interface to
quickly operationalize workflows into production settings

12. 12© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
SageMaker Data Wrangler
Use Cases
Cleanse & Explore Data
Use built-in data transformations to
accelerate data cleansing and
exploration
Visualize & Understand Data Enrich Data
Quickly detect outliers or
extreme values within a data set
without the need to write code
Use built-in data transformation tools to
transform data into formats that can be
used to build accurate ML models

13. 13© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Quickly select and query data
Select data from Amazon Athena,
Amazon Redshift, AWS Lake
Formation, Amazon S3, and features
from SageMaker Feature Store
Write queries for data sources before
importing data over to SageMaker
Data Wrangler
Import data in various file formats,
such as CSV files, Parquet files, and
database tables directly into Amazon
SageMaker

14. 14© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Easily transform data
Transform your data without writing a
single line of code using over 300 built-in
data transformations
Built-in data transformations include
convert column type, rename column, and
delete column
Author custom transformations in
PySpark, SQL, and Pandas

15. 15© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Understand your data visually
Intuitively understand your data with a set
of pre-configured visualization templates
Pre-configured visualization templates
include histograms, scatter plots, box and
whisker plots, line plots, and bar charts
Interactively create and edit your own
visualizations so you can quickly detect
outliers or extreme values

16. 16© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Quickly estimate model accuracy
Identify inconsistencies in data
preparation workflows and diagnose
issues before ML models are deployed
into production
Select subsets of data to identify errors
Identify which features are contributing
to model performance relative to others
Determine if additional feature
engineering is needed to improve model
performance

17. 17© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Deploy data preparation workflows into production
Export data preparation workflows to a
notebook or Python code
Integrate your workflow with
SageMaker Pipelines to automate
model deployment and management
Publish created features to SageMaker
Feature Store for reuse and syndication
across teams and projects

18. 18© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Amazon SageMaker
Debugger
Detect bottlenecks and
training problems in real-time,
and train models faster
Detect bottlenecks and issues during training in real-time and correct problems
to deploy models faster, with a single, unified tool
Generate ML models faster
Monitor and profile system resources without code, and get
recommendations to optimize resources effectively
Optimize resources with no additional code
Get complete insights into the ML training process in real-time and offline
Make ML training transparent

19. 19© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Automatic detection of errors with visualization of alerts
1
2 Alerts to resolve errors during ML training runs
Automatic detection of common training errors such as gradient values
becoming too large or too small
3 Visualization of alerts with Amazon SageMaker Studio or with the
SageMaker Debugger SDK

20. 20© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Monitor and profile system resource utilization
Automatically monitor system
resource utilization
Profile training jobs to collect ML
framework metrics
Visualize system resource utilization
for GPU, CPU, network, memory
within SageMaker Studio

21. 21© 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Analyze errors and take action
Built-in analysis in the form of
rules
Automatically analyze training
data including inputs, outputs,
tensors
Detect if a model is overfitting or
overtraining, or determine if
gradient values are not correct
Specify custom actions to stop
training or send alerts

22. © 2021, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Deep
Learning
AMIs &
Containers
GPUs &
CPUs
Elastic
Inference
Trainium Inferentia FPGA
FRAMEWORKS & INFRASTRUCTURE
DeepGraphLibrary
Frameworks & Infrastructure

23. © 2021, Amazon Web Services, Inc. or its affiliates. All rights reserved.
DRAFT
Habana-based instances
C O M I N G 2 0 2 1
EC2 instances powered by accelerator chips named
Habana Gaudi from Habana Labs, an Intel company
Compute
Coming 2021

24. © 2021, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Most TFLOPS compute power vs. any other machine
learning instance in the cloud
Use the same Neuron SDK as Inferentia instances
DRAFT
AWS Trainium
C O M I N G 2 0 2 1
First ML chip for training—will be the most cost effective in the cloud
Compute
Coming 2021

25. Thank you!
© 2021, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Chris Fregly
Twitter @cfregly
Antje Barth
Twitter @anbarth
https://www.amazon.com
/dp/1492079391/