Catch lightning in a bottle: How to use image classification on Snowflake using deep learning

Catch a glimpse of how deep learning models can be deployed directly on Snowflake using Python UDFs. This blog walks you through training a Convolutional Neural Network (CNN) for image classification. Experience the power of combining SQL, unstructured data, and real-time inference—right inside Snowflake.

BLOGS

2/26/20251 min read

green and red light wallpaper
green and red light wallpaper

This blog explores unstructured data handling and real-time image classification on Snowflake.
A CNN model is trained locally with TensorFlow, then packaged as an H5 file for streamlined deployment.
Python UDFs enable direct model invocation via standard SQL queries, seamlessly integrating deep learning with data warehousing.
This setup consolidates MLOps into one environment, simplifying model deployment and maintenance.
Images are uploaded, processed, and classified within Snowflake, bridging the gap between analytics and AI-driven insights.
Deep learning becomes readily operational through Snowflake’s robust platform, removing the need for separate systems.

This blog is owned by LTIMindtree.
Read the full article here: Catch lightning in a bottle