Learn how to run LandingLens model inferences directly in Snowflake using SQL. Use the core.run_inferences() function to perform both batch and single-image inference on your datasets. Then insert the inferences as structured data into a new Snowflake table. More...
This video demonstrates how to use LandingLens to train a computer vision model for a multiclass classification project using an open-access retinopathy of prematurity dataset. It covers the end-to-end process, including data preparation, model training with custom...
Unlock the full potential of LandingLens and Snowflake by building custom, secure Streamlit apps for image review, MLOps, dashboards and other applications. Learn how to integrate image inference data with structured datasets, build interactive applications, and drive...
Learn how to improve your vision model’s performance in LandingLens by integrating human judgment into the machine learning workflow. Discover how to review predictions, prioritize critical errors, and use expert feedback to drive continuous improvement and refine...
In this tutorial video, discover four ways of evaluating the performance of a Classification computer vision model in LandingLens on Snowflake: Model metrics such as F1, Precision and Recall Confusion matrix, confidence scores and visual inspection of...
