The document discusses a presentation by Samuel James on building a recommendation engine using image recognition technology on AWS, focusing on the importance and workings of recommender systems. It highlights Architrave GmbH's achievements as a proptech company and provides insights into various filtering techniques such as collaborative, content-based, and hybrid filtering. The talk emphasizes leveraging AWS Rekognition for analyzing unstructured data and the benefits of using AWS for developing AI capabilities in applications.

1. Samuel James | 09.09.2019
Community Day 2019 Sponsors
Build a Powerful Recommendation Engine Using Image
Recognition Technology on AWS

2. About Architrave Gmbh
PropTech Company of the year 2018
Over 3,900 managed assets worth €80 billion
Over €12 billion in annual transaction volume
(including Germany's largest single transactions:
Sony Centre 2017 and Frankfurt Omni Tower 2018)
! Berlin ! Frankfurt! Dresden

3. What This Talk is Not About
Recommender Systems’ Algorithms

4. Agenda
Recommendation system
Why recommender systems are important
How recommendation engines work
Leveraging on AWS Rekognition for product recommendation
Demo

5. What Is Recommendation ?
Recommendation is about providing relevant content to
the user based on knowledge of the user, content, and
interactions between the user and items.

6. !6

7. !7
According to McKinsey & Company, 35% of
Amazon.com’s revenue is generated by its
recommendation engine

8. !8
"Netflix saves up to $1 billion a year via its personalised
recommendations”
– Business Insider

9. !9
Personalised recommendations drive sales

10. Recommendation Phases
Data
Collection
Data Storage Data Analysis Data Filtering

11. Collaborative Filtering
Content-Based Filtering
Hybrid Filtering
Data Filtering Techniques

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

13. Collaborative Filtering Technique in a Retail Site

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

15. Content-Based Filtering Technique in a Retail Site

16. Hybrid Filtering
Combines collaborative filtering and content-based filtering.

17. !17
Leveraging on AWS Rekognition API for analysis of
unstructured data like images

18. AWS Rekognition at a Glance

19. !19

20. !20

21. !21
DEMO

22. Using S3 Batch Operations

23. Handling new Uploads

24. !24

25. !25
How the visual search works

26. !26

27. Lessons Learned
Building with AWS reduces your development time
You don't need to be AI experts to have AI capability in your app
Build a repeatable and reusable infrastructure with AWS

28. !28
Thanks!
Questions?
Contact
Architrave GmbH
Bouchéstraße 12,
Building 1A, 12435 Berlin
Samuel James
Samuel James
Email: james@architrave.de
@samuelabiodunj