ML Sidekick, a no-code app built using Streamlit in Snowflake, designed for building and deploying machine learning models in Snowflake. This application aids both seasoned data scientists and business users with no coding experience by simplifying the machine learning process and making it accessible to a broader audience. This applications provides features for:
- Selection and preprocessing of data to build machine learning models
- Training and evaluation machine learning models within the Snowflake environment
- Logging models to Snowflake model registry
- Generation python code for the pipeline in form a notebook
- Exploration/comparison different versions of registered models or different models
For prerequisites, environment setup, step-by-step guide and instructions, please refer to the QuickStart Guide