https://github.com/adamduval/ml_snowflake_end_to_end

❄️ End to End ML workflow in Snowflake.
https://github.com/adamduval/ml_snowflake_end_to_end

machine-learning python snowflake sql streamlit

Last synced: 20 days ago
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❄️ End to End ML workflow in Snowflake.

• Host: GitHub
• URL: https://github.com/adamduval/ml_snowflake_end_to_end
• Owner: adamduval
• Created: 2024-09-10T14:48:12.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2025-01-09T13:25:37.000Z (about 1 month ago)
• Last Synced: 2025-01-09T14:38:18.380Z (about 1 month ago)
• Topics: machine-learning, python, snowflake, sql, streamlit
• Language: Jupyter Notebook
• Homepage:
• Size: 107 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# End-to-End Workflow in Snowflake ML

Companion code for Unlocking Rapid Insights with an End-to-End Workflow in Snowflake ML at Cooke Aquaculture Medium Article.

The article can be found [here](https://medium.com/snowflake/from-zero-to-value-unlocking-rapid-insights-with-an-end-to-end-ml-workflow-in-snowflake-9b000a25723c)

The notebooks follow and entire ML project flowusing the Snowflake Ecosystem. The process includes:

1. EDA

2. Data Engineering

3. Baseline Modeling

4. Feature Engineering

5. Advanced Model Development

6. Model Deployment and MLOps

7. Model Delivery