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Getting Started with Machine Learning on AWS

M
Mike Fowler

The document presents an introduction to machine learning, covering concepts like models, feature engineering, and training processes. It discusses the AWS machine learning stack and presents various use cases, such as audio description for images and solving sudoku puzzles. The document also emphasizes the importance of identifying problems to solve and sourcing relevant data.

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@mlfowler_ @Claranet Getting Started with Machine Learning Mike Fowler - Senior Site Reliability Engineer - Public Cloud Practice PLACE CUSTOMER LOGO HERE
London PostgreSQL Meetup January 24th 2019 About MeAbout Me
@mlfowler_ @Claranet
@mlfowler_ @Claranet • What is Machine Learning? • The AWS Machine Learning Stack • ML Use Cases • Machine Learning: The Forgotten Service Agenda
@mlfowler_ @Claranet Ethics Source: https://peakcare.wordpress.com/2011/10/05/heads-in-the-sand/
@mlfowler_ @Claranet What is … Machine Learning?
@mlfowler_ @Claranet How do Machines Learn? Source: https://towardsdatascience.com/machine-learning-types-2-c1291d4f04b1
@mlfowler_ @Claranet Machine Learning Concepts • Models - Mathematical equation with a solution space approximating the outputs for the given inputs • Feature Engineering - Process of identifying & creating features from the data that will influence/assist the model • Training - Repeated process attempting to find the model that is “just right” such that it does not overfit or underfit the training data
@mlfowler_ @Claranet Dang it Jim, I’m an Engineer not a Mathematician!
@mlfowler_ @Claranet The AWS Machine Learning Stack
@mlfowler_ @Claranet Categories of ML Services
@mlfowler_ @Claranet Categories of ML: Ready to Eat Amazon Comprehend Amazon Polly Amazon Rekognition Amazon Textract Amazon Transcribe Amazon Translate
@mlfowler_ @Claranet Use Case: Audio Description for Images
@mlfowler_ @Claranet Use Case: Audio Description for Images Lambda
@mlfowler_ @Claranet Use Case: Audio Description for Images Rekognition Image Lambda
@mlfowler_ @Claranet Use Case: Audio Description for Images PollyRekognition Image Lambda
@mlfowler_ @Claranet Use Case: Solving Sudoku Puzzles
@mlfowler_ @Claranet Use Case: Solving Sudoku Puzzles S3
@mlfowler_ @Claranet Use Case: Solving Sudoku Puzzles S3 Lambda
@mlfowler_ @Claranet Use Case: Solving Sudoku Puzzles S3 Rekognition Text in Image Lambda
@mlfowler_ @Claranet Use Case: Solving Sudoku Puzzles
@mlfowler_ @Claranet Use Case: Solving Sudoku Puzzles
@mlfowler_ @Claranet Use Case: Solving Sudoku Puzzles
@mlfowler_ @Claranet Use Case: Solving Sudoku Puzzles Have a Play! http://bit.ly/comsumsudoku https://github.com/gh-mlfowler/sudokusolve
@mlfowler_ @Claranet Categories of ML: Part Baked Amazon Forecast Amazon Personalize
@mlfowler_ @Claranet The Forgotten Service
@mlfowler_ @Claranet Scene: Being On Call https://www.silicon.co.uk/wp-content/uploads/2017/02/Pager.jpg
@mlfowler_ @Claranet Scene: Our Engineer Rests Peacefully Source: https://peakcare.wordpress.com/2011/10/05/heads-in-the-sand/https://i.pinimg.com/originals/cb/32/5f/cb325f9c268bf2135125f512d95
@mlfowler_ @Claranet Engineer RestingScene: Red Alert! Source: https://peakcare.wordpress.com/2011/10/05/heads-in-the-sand/https://vignette.wikia.nocookie.net/memoryalpha/images/6/6b/RedAlert.jpg/revision/latest?cb=20100117050244&path-prefix=en
@mlfowler_ @Claranet Scene: Peace Source: https://peakcare.wordpress.com/2011/10/05/heads-in-the-sand/ https://www.lakelouiseinn.com/wp-content/uploads/2019/01/LakeLouise2-1.jpg
@mlfowler_ @Claranet
@mlfowler_ @Claranet Identify a Problem to Solve Many PagerDuty incidents resolve before I respond disrupting my sleep needlessly
@mlfowler_ @Claranet Source Relevant Data
@mlfowler_ @Claranet Input Data
@mlfowler_ @Claranet Input Data
@mlfowler_ @Claranet Target
@mlfowler_ @Claranet Target
@mlfowler_ @Claranet Target
@mlfowler_ @Claranet Train the Model
@mlfowler_ @Claranet The Lambda Architecture Master Data Serving LayerBatch Layer Speed Layer S3 EMR Kinesis Streams Glue Redshift (Batched Views) DynamoDB (Real-Time Views)
@mlfowler_ @Claranet ML Model The Lambda Architecture + ML Master Data Serving LayerBatch Layer Speed Layer S3 EMR Kinesis Streams Glue Redshift (Batched Views) DynamoDB (Real-Time Views) Amazon Machine Learning
@mlfowler_ @Claranet Make Predictions
@mlfowler_ @Claranet Make Predictions
@mlfowler_ @Claranet Make Predictions
@mlfowler_ @Claranet Make Predictions
@mlfowler_ @Claranet Categories of ML: Raw Ingredients Amazon SageMaker Amazon Elastic Inference Amazon SageMaker Ground Truth AWS Deep Learning AMIs Apache MXNet on AWS TensorFlow on AWS
@mlfowler_ @Claranet Feature Engineering • Most models only take numeric input • Values often need to be constrained - Scale Min/Max - Logarithm • Some values can’t be used - Identifiers - Attributes that wouldn’t be known when making a prediction
@mlfowler_ @Claranet Fin
@mlfowler_ @Claranet Questions ? Have a Play! http://bit.ly/comsumsudoku https://github.com/gh-mlfowler/sudokusolve
Getting Started with Machine Learning on AWS

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Getting Started with Machine Learning on AWS