You’ve always thought you looked like Marty McFly but your friends say you look like Yoda, take the 80s doppleganger challenge and find out for sure! In this talk, I’ll show how to use a little bit of machine learning and serverless tech to build an application that can match faces to their dopplegangers. All written with Angular and Node!

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Machine learning is a
data science technique that
allows computers to use
existing data to forecast future
behaviors, outcomes and
trends

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Machine learning
Vs
Traditional computing

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ML
Algorithm
Data Model
New
Data
Predict
Results

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Model
A mathematical object describing the
relationship between the features and the
target

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Doppelgänger
App

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Step 1

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Step 1
Data
Ingestion
and
Preparation

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Step 2

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Step 2
Train
The Model

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Step 3

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Step 3
Model
deployment

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Custom Vision
Service
Tool for building
custom image
classifiers

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Demo

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Of the pictures classified as Luke Skywalker,
How many are actually Luke?
Precision:
Of the pictures that are actually of Luke Skywalker,
How many are classified Luke?
Recall:

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Angular

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Goal achieved 😍

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Automation

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Tasks
Get a list of URLs for each tag
Send that list to our model to train on

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Serverless architectures refer to
applications that significantly depend on
third-party services (known as Backend as
a Service or “BaaS") or on custom code
that's run in ephemeral containers
(Function as a Service or "FaaS")”
–Martin Fowler

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Reacts to events
Autoscales
Pay as you go
Serverless

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Lorraine Baines
Bing Image
Search
API
{
name: Lorraine Baines
url: <some_url>
}
{
TagIds: [<some_tag>]
Urls: [<some_url>]
}
Training
API

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Lorraine Baines
Bing Image
Search
API
{
name: Lorraine Baines
url: <some_url>
}
{
TagIds: [<some_tag>]
Urls: [<some_url>]
}
Training
API

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HTTPS://AKA.MS/80S

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Resources
https://github.com/simonaco/
doppelganger-api
https://github.com/simonaco/
doppelganger
https://aka.ms/functions
https://aka.ms/try-cvs
Source code model training and
prediction API
Source code UI
Azure Functions documentation
Azure Custom Vision Service
documentation

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Thank
you!