predictive analytics: getting started with amazon machine learning
TRANSCRIPT
©2015, Amazon Web Services, Inc. or its affiliates. All rights reserved
Getting Started with Machine Learning
Guy Ernest, BDM [email protected]
Main Takeaways
• Machine Learning is a focus in Amazon• ML is big and growing• ML is easy and will be used by everyone
How to be successful in Business
E*BI
RTML
EC2ECSElastic Beanstalk
RedshiftEMR
KinesisElasticSearch
Amazon MLSpark ML
What do your kids learn in Math Class
4 Steps to Solving Math Problems
• Posing the right question• Real world to computation formulation• Computation• Computation formulation to the real world
4 Steps to Solving Math ML Problems
• Posing the right question• Real world to computation formulation• Computation• Computation formulation to the real world
=Data
=Application
=Business Problem
The circle of ML
Application
E*
Data
Model Customer
Front end team
Data Engineering team
Analysts / DS team
DevOps team
And a few more examples…
Fraud detection Detecting fraudulent transactions, filtering spam emails, flagging suspicious reviews, …
Personalization Recommending content, predictive content loading, improving user experience, …
Targeted marketing Matching customers and offers, choosing marketing campaigns, cross-selling and up-selling, …
Content classification Categorizing documents, matching hiring managers and resumes, …
Churn prediction Finding customers who are likely to stop using the service, upgrade targeting, …
Customer support Predictive routing of customer emails, social media listening, …
What do you need to know to use Machine Learning?
ML Model is a function to split Space
Historical Data Model Building Prediction
What is my color?
And what is mine?
Why more data is better?
Less Data More Data Even More Data
Why more attributes are better?
Less Attributes More Attributes Even More Attributes
Where to Split?
Data
Engineering
Why Clean Data is better?
Messy Data Cleaner Data Fantasy Data
Gray Area
Recall and Precision
• Which mistake do you prefer?
Linear Regression
Parameters ComplexityLow complexitySparse Data
High complexityDense Data
Neural Networks
Speech Recognition
Face recognition
OCRThe Face Neuron
Machine Translation
こんにちはשלוםEvent/Doc
Classification
Light ML Amazon ML Statistical ML Deep Learning
Images
Input
Natural Language
Your Fortune Cookie
“Stop writing heuristic code, and start building predictive models”