Learn how to build an end-to-end smart application in the AWS Cloud in this webinar on Amazon Machine Learning (Amazon ML). During the session, we will show you how to create machine learning models, deploy them to production and obtain predictions in real-time. We will also walk you through the process of building a complete smart application using Amazon ML, AWS IoT and AWS Lambda, as well as covering the process flow, architecture and code needed for Amazon ML implementation. With information about using Amazon ML and integrating it into your applications, this session will prepare you to take full advantage of predictive analytics in the cloud.

1. Building Smart Applications
with Amazon Machine
Learning
Neeraj Kumar, Enterprise Solutions Architect

2. Learning objectives for this session
Learn about AWS services needed to build smart IoT applications
on AWS – Amazon Machine Learning, AWS IoT & AWS Lambda

3. At Amazon, we’ve been making investments in ML
for the last 20 years…
Search &
Discovery
Fulfilment &
Logistics
Existing
Products
New
Initiatives

4. Running ML in Production on AWS Today

5. ”
“
Fraud.net Uses AWS to Quickly, Easily Detect Online Fraud
Fraud.net is the world’s leading crowdsourced
fraud prevention platform.
Amazon Machine Learning
helps us reduce complexity
and make sense of emerging
fraud patterns.
• Needed to build and train a larger number of more
targeted and precise machine-learning models
• Uses Amazon Machine Learning to provide more than
20 machine-learning models
• Easily builds and trains machine-learning models to
effectively detect online payment fraud
• Reduces complexity and makes sense of emerging
fraud patterns
• Saves clients $1 million weekly by helping them detect
and prevent fraud
Oliver Clark
CTO,
Fraud.net
”
“

6. Amazon AI: Democratizing Artificial Intelligence
AI Services
AI Platform
Amazon
Rekognition
Amazon
Polly
Amazon
Lex
More to come
in 2017
Amazon
Machine Learning
Amazon Elastic
MapReduce
Spark &
SparkML
More to come
in 2017
AI EnginesApache
MXNet
Caffe Theano KerasTorch CNTKTensorFlow
P2 ECS Lambda GreenGrass FPGAEMR/Spark
More to
come
in 2017
Hardware

7. Amazon Machine Learning
Create ML models without having to learn complex
algorithms and technology

8. Train and optimize models on GBs of data
Batch process predictions
Real-time prediction API in one-click
No servers to provision or manage
Easy to use, high performance

9. Three supported types of predictions
Binary classification
Predict the answer to a Yes/No question
Multiclass classification
Predict the correct category from a list
Regression
Predict the value of a numeric variable

10. Train
model
Evaluate &
optimize
Make
predictions
1 2 3
Development process

11. Model Evaluation and Optimization

12. AWS IoT

13. Hands-on Demo
AWS Lambda
Device Gateway
Amazon Machine
Learning
windturbine/telemetry
IoT
rule
Device Shadow
AWS IoT
Wind Farm

14. Thank you!