Recommendation Engine Pipeline with BigQuery ML and Vertex AI Pipelines using Matrix Factorization | C2C Community

Recommendation Engine Pipeline with BigQuery ML and Vertex AI Pipelines using Matrix Factorization

  • 17 August 2022
  • 2 replies
  • 48 views

Userlevel 7
Badge +19

The use of matrix factorizations in recommendation systems is widely. If you want to quickly and easily develop a solution to provide excellent recommendations to your clients, then you will get  a good and simple starting point from this video:

 

 

The above video contains following content :

00:00 Introduction

00:49 Pipeline

01:28  Dependencies

02:20 Data

02:55 Why reservations

04:10 Create slots

08:31 Delete slots

09:00 Train model

10:40 Deployment

12:24 Serving

12:47 Running Pipeline

14:40 Deployment

16:04 Recommendations

 

Extra supporting credit:

Check out the two Google articles if you're new to matrix factorization and BigQuery ML.

 

Note:

The data used in the video demonstration and the Google BigQuery ML examples are identical. No need to reinvent the wheel in this case.


2 replies

Userlevel 7
Badge +16

Great post, @malamin , thanks a lot! 

Userlevel 7
Badge +19

My pleasure @Dimitris Petrakis 

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