Snowpark brings deeply integrated, DataFrame-style programming to the languages developers like to use, and functions to help them build and deploy custom programs including machine learning models. And to bring predictive insights into actions, data scientists can build interactive applications that business stakeholders can use to interact with those models using Streamlit!
We will show why Snowpark and Streamlit are the perfect match for Python developers. We will go through:
Introduction to Snowpark for Python Setting up your favorite IDE (e.g. Jupyter) for Snowpark Creating and registering Python user-defined functions using open-source libraries with near-zero maintenance or overhead Building Streamlit app and use Snowpark UDFs