Product Enrichment and Recommender Systems // Marc Lindner and Amr Mashlah // Coffee Sessions #114

1

Introduction

00:00 • 2min

2

The Challenges of Recommendation Systems

01:36 • 2min

3

The Core Challenges of a Recommender Systems Podcast

03:38 • 2min

4

Easy Life

06:02 • 2min

5

Is It Possible to Recommend Good Things on Netflix?

08:29 • 2min

6

Feature Based Approach or Collaborative Filtering Approach?

10:26 • 3min

7

The Challenges in Generating Multimodal Recommendation?

12:57 • 3min

8

Scaling Models on AWS?

15:35 • 3min

9

How Do You Handle Multi-Modal Recommendation?

18:18 • 2min

10

Do You Think You Can Ingest All This Data?

20:11 • 2min

11

Scaling Up a Multimodal Recommendation Model

22:32 • 2min

12

Using the User Preferences on Movies, Movies and Music

24:10 • 2min

13

The Difference Between the Three Major Things Is Like Purely Category Focused

25:51 • 2min

14

How Do You Handle Cold Start?

27:31 • 2min

15

We Found That Text Embedings Really Improved Productivity and That's Awesome, Right?

29:10 • 3min

16

Is There Really a Bad Recommendation?

31:42 • 3min

17

Is There a Way to Improve the Onboarding Process?

34:31 • 3min

18

How Does Curation Work in a Recommendation System?

37:46 • 3min

19

Are You Using Social Features in Your App?

40:18 • 2min

20

Rexis - What's Next on the Roadmap?

42:20 • 3min

21

The Ultimate Travel Companion

45:44 • 2min

22

The Ocean Model

48:01 • 4min

23

Are You Getting a Good Relationship With Your Ads?

52:08 • 3min

24

The Ultimate Travel Companion - Skylare

54:46 • 2min