Build a serverless recommendation engine in 72 hours

Transcript

1. Build a serverless recommendation engine in 72 hours
   @samueljabiodun | Samuel James
   

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2. @samueljabiodun
   Who Am I?
   − AWS Solutions Architect (Associate)
   − Software Engineer @ Architrave Gmbh
   ✦ PropTech company of the year 2018
   ✦ Over €12 billion in annual transaction volume (including Germany's largest
   single transactions: Sony Centre 2017 & Frankfurt Omni Tower 2018)
   ✦ Over 3,900 managed assets worth €80 billion

   − Technical Author @ HitSubscribe
   

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3. @samueljabiodun
   “At some point we’re going to see the first billion-dollar
   startup with a single employee, the founder, and that
   engineer will be using serverless."
   James Governor
   Co-founder at RedMonk
   

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4. @samueljabiodun
   In the beginning …
   

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5. @samueljabiodun
   Physical Machine
   ❏ Install and configure tons of packages to get your
   application up and run
   ❏ Very Expensive
   ❏ Scaling was an hassle
   ❏ Maintenance was still a problem
   

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6. @samueljabiodun
   

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7. @samueljabiodun
   Code
   Runtime
   OS
   Hardware
   Physical Servers
   

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8. @samueljabiodun
   Code
   Runtime
   OS
   Hardware
   Physical Servers
   Code
   Runtime
   OS
   Hardware
   Virtual Machines
   Code
   Runtime
   OS
   Hardware
   Code
   Runtime
   OS
   Hardware
   Serverless
   Containers
   

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9. @samueljabiodun
   Code
   Runtime
   OS
   Hardware
   Serverless
   Serverless

   …computing model that allows you to build
   and run code at scale without thinking about
   servers or infrastructures
   

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10. @samueljabiodun
    Serverless and PaaS

    What is the difference?
    

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11. @samueljabiodun
    − Scaling
    − Composition
    − Idle State
    Why PaaS Is Not Serverless (FaaS)
    

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12. @samueljabiodun
    − Scaling
    − Composition
    − Idle State
    Why PaaS Is Not Serverless (FaaS)
    

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13. @samueljabiodun
    Business Logic
    

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14. @samueljabiodun
    − Scaling
    − Composition
    − Idle State
    Why PaaS Is Not Serverless (FaaS)
    

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15. @samueljabiodun
    Why going serverless?
    − No server provisioning
    − Pay for usage only
    − Infinite scale
    − No server management
    − Quicker time to market
    − Monitoring and logging out of the box
    

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16. @samueljabiodun
    "There is no silver bullet. There are
    always options and the options have
    consequences”

    - Ben Horowitz
    

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17. @samueljabiodun
    Use cases
    − Data processing (Images,
    Videos etc)
    − Scalable static websites
    − Mobile backends
    − Real-time analysis
    − IoTs
    − Event streaming applications
    − Multi-lingual applications
    − And more…
    

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18. @samueljabiodun
    Serverless Recommendation Engine
    

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19. @samueljabiodun
    

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20. @samueljabiodun
    

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21. @samueljabiodun
    Recommendation is about suggesting relevant
    products to your users based on the knowledge
    you have users, products, and users' interactions
    with your products
    

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22. @samueljabiodun
    Recommendation is all about data
    

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23. @samueljabiodun
    

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24. @samueljabiodun
    

    According to McKinsey & Company, 35%
    of Amazon.com’s revenue is generated by
    its recommendation engine.
    

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25. @samueljabiodun
    "Netflix saves up to $1 billion a year via
    its personalised recommendations” 

    

    – Business Insider
    

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26. @samueljabiodun
    Personalised recommendations drive
    sales
    

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27. @samueljabiodun
    Data
    Collection
    Data Storage Data Analysis Data Filtering
    Recommendation Phases
    

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28. @samueljabiodun
    Data Filtering Techniques
    − Collaborative Filtering
    − Content-Based Filtering
    − Hybrid Filtering
    

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29. @samueljabiodun
    Collaborative Filtering
    Interactions of users with products (like movies
    watched, products viewed, products bought etc.
    

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30. @samueljabiodun
    Collaborative Filtering Technique in a
    Retail Site
    

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31. @samueljabiodun
    

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32. @samueljabiodun
    

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33. @samueljabiodun
    Content-based Filtering
    Focuses on properties of items. Similarity of items
    is determined by measuring the similarity in their
    properties.
    

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34. @samueljabiodun
    Content-based Filtering Technique in a
    Retail Site
    

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35. @samueljabiodun
    AWS Rekognition At A Glance
    

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36. @samueljabiodun
    

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37. @samueljabiodun
    

    Analysing existing (millions,
    billions of) objects on S3 using
    AWS Batch
    

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38. @samueljabiodun
    

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39. @samueljabiodun
    Hybrid Filtering
    Combines collaborative filtering and content-
    based filtering
    

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40. @samueljabiodun
    Learn about
    your users
    Gain insights in
    to your products
    

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41. @samueljabiodun
    Users do search for products
    too, how about adding a visual
    search?
    

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42. @samueljabiodun
    

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43. @samueljabiodun
    DEMO
    

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44. @samueljabiodun
    

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45. @samueljabiodun
    Summary
    − Serverless reduces your development time
    − With Serverless, you do not need to be an AI expert to have AI capabilities in your
    app
    

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46. @samueljabiodun
    

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47. @samueljabiodun
    Thanks!

    Questions?
    

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