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Build, train and deploy ML models using Amazon SageMaker
The Amazon Machine Learning Stack
PLATFORM SERVICES
APPLICATION SERVICES
FRAMEWORKS & INTERFACES
Caffe2 CNTK
Apache
MXNet
PyTorch TensorFlow Chainer Keras Gluon
AWS Deep Learning AMIs
Amazon SageMaker
Rekognition Transcribe Translate Polly Comprehend Lex
AWS
DeepLens
EDUCATION
Amazon Mechanical Turk
What is Amazon SageMaker?
Amazon SageMaker
A fully-managed platform
that provides the quickest and easiest way for
data scientists and developers to get
ML models from idea to production.
Amazon SageMaker components
Amazon’s fast, scalable algorithms
Distributed TensorFlow, Apache MXNet, Chainer, PyTorch
Bring your own algorithm
Hyperparameter Tuning
Building HostingTraining
Amazon SageMaker components
Amazon’s fast, scalable algorithms
Distributed TensorFlow, Apache MXNet, Chainer, PyTorch
Bring your own algorithm
Hyperparameter Tuning
Building HostingTraining
Building
… or Apache Spark
through EMR and
the SageMaker
Spark SDK...
Use SageMaker‘s
hosted Notebook
Instances...
... or the Console
for a point and
click experience...
... or your own
device (EC2,
laptop, etc.)
Amazon SageMaker components
Amazon’s fast, scalable algorithms
Distributed TensorFlow, Apache MXNet, Chainer, PyTorch
Bring your own algorithm
Hyperparameter Tuning
Building HostingTraining
Training
Zero setup Streaming
datasets +
distributed
compute
Docker / ECS Deploy trained
models locally or to
Amazon SageMaker,
AWS Greengrass, AWS
DeepLens
Amazon SageMaker components
Amazon’s fast, scalable algorithms
Distributed TensorFlow, Apache MXNet, Chainer, PyTorch
Bring your own algorithm
Hyperparameter Tuning
Building HostingTraining
Hosting
One-click
deployment
Low latency, high
throughput, and
high reliability
A/B testing Bring your own
model
Amazon SageMaker components
Amazon’s fast, scalable algorithms
Distributed TensorFlow, Apache MXNet, Chainer, PyTorch
Bring your own algorithm
Hyperparameter Tuning
Building HostingTraining
Built-in algorithms
XGBoost, FM,
Linear, and
Forecasting
for supervised
learning
Kmeans, PCA,
and Word2Vec
for clustering
and pre-
processing
Image
classification
with
convolutional
neural networks
LDA and NTM
for topic
modeling,
seq2seq for
translation
Amazon SageMaker components
Amazon’s fast, scalable algorithms
Distributed TensorFlow, Apache MXNet, Chainer, PyTorch
Bring your own algorithm
Hyperparameter Tuning
Building HostingTraining
TensorFlow and Apache MXNet Docker Containers
… explore and
refine models in a
single Notebook
instance
… deploy to
production
Sample your
data… Use the same code
to train on the full
dataset in a cluster
of instances…
Amazon SageMaker components
Amazon’s fast, scalable algorithms
Distributed TensorFlow, Apache MXNet, Chainer, PyTorch
Bring your own algorithm
Hyperparameter Tuning
Building HostingTraining
Bring your own algorithm
... add algorithm
code to a Docker
container...
Pick your
preferred
framework...
... publish to ECS
Amazon ECS
Amazon SageMaker components
Amazon’s fast, scalable algorithms
Distributed TensorFlow, Apache MXNet, Chainer, PyTorch
Bring your own algorithm
Hyperparameter Tuning
Building HostingTraining
Hyperparameter Tuning
(Automated Model Tuning)
Run a large set of training
jobs with varying
hyperparameters...
... and search the
hyperparameter space for
improved accuracy.
Zero setup for data exploration
Resizable as you
need
Common tools
pre-installed
Easy access to
your data sources
No servers to
manage
M o d u l a r a r c h i t e c t u r e
Past
Data
Training
algorithm
Model
artifacts
Inference
code
Client
application
Model
Data
Inference
Ground
truth
Amazon SageMaker
Pay as you go and inexpensive
ML compute by the
second starting
at $0.0464/hr
ML storage by the
second
at $0.14
per GB-month
Data processed in
notebooks and hosting
at $0.016 per GB
Free trial to get started
quickly
Getting Started
https://console.aws.amazon.com/sagemaker
Start with sample notebooks
Modify to access your data sources
Train your model
Deploy your model
Perform inferences
Demo:
Neural networks and embeddings
for recommendations
Demo:
Bringing your own algorithm
Get Started today with Amazon
SageMaker
https://console.aws.amazon.com/sagemaker
Questions?
Thanks!

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Build, Train, & Deploy ML Models Using SageMaker