predictive analytics: getting started with amazon machine learning
TRANSCRIPT
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©2015, Amazon Web Services, Inc. or its affiliates. All rights reserved
Getting Started with Machine Learning
Guy Ernest, BDM [email protected]
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Main Takeaways
• Machine Learning is a focus in Amazon• ML is big and growing• ML is easy and will be used by everyone
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How to be successful in Business
E*BI
RTML
EC2ECSElastic Beanstalk
RedshiftEMR
KinesisElasticSearch
Amazon MLSpark ML
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What do your kids learn in Math Class
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4 Steps to Solving Math Problems
• Posing the right question• Real world to computation formulation• Computation• Computation formulation to the real world
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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
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The circle of ML
Application
E*
Data
Model Customer
Front end team
Data Engineering team
Analysts / DS team
DevOps team
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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, …
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What do you need to know to use Machine Learning?
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ML Model is a function to split Space
Historical Data Model Building Prediction
What is my color?
And what is mine?
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Why more data is better?
Less Data More Data Even More Data
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Why more attributes are better?
Less Attributes More Attributes Even More Attributes
Where to Split?
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Data
Engineering
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Why Clean Data is better?
Messy Data Cleaner Data Fantasy Data
Gray Area
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Recall and Precision
• Which mistake do you prefer?
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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
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Your Fortune Cookie
“Stop writing heuristic code, and start building predictive models”