Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Build a serverless recommendation engine in 72 hours

Build a serverless recommendation engine in 72 hours

Samuel James

October 16, 2019

More Decks by Samuel James

Other Decks in Technology


  1. @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
  2. @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
  3. @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
  4. @samueljabiodun Code Runtime OS Hardware Physical Servers Code Runtime OS

    Hardware Virtual Machines Code Runtime OS Hardware Code Runtime OS Hardware Serverless Containers
  5. @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
  6. @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
  7. @samueljabiodun "There is no silver bullet. There are always options

    and the options have consequences”
 - Ben Horowitz
  8. @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…
  9. @samueljabiodun Recommendation is about suggesting relevant products to your users

    based on the knowledge you have users, products, and users' interactions with your products
  10. @samueljabiodun 
 According to McKinsey & Company, 35% of Amazon.com’s

    revenue is generated by its recommendation engine.
  11. @samueljabiodun "Netflix saves up to $1 billion a year via

    its personalised recommendations” 
 – Business Insider
  12. @samueljabiodun Content-based Filtering Focuses on properties of items. Similarity of

    items is determined by measuring the similarity in their properties.
  13. @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