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

Опубликовано: 08 Июль 2022
на канале: ML Engineer
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Matrix factorizations are widely used for Recommendation Systems. They are a great and easy starting point if you want to build a quick and easy solution to deliver great recommendations to your customers.

📓 Notebook: https://colab.research.google.com/dri...
📖 Article:   / recommendations-pipeline-with-matrix-facto...  

If you’re new to BigQuery ML and matrix factorization, check the two articles from Google.

Recommendations with implicit feedback https://cloud.google.com/bigquery-ml/...
Recommendations with explicit feedback
https://cloud.google.com/bigquery-ml/...

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▬ Timestamps ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
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
16:45 Thanks BYE


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