In this quickstart, you will use the Snowflake Model Registry to implement partitioned training and inference using custom models. When using the model, the registry partitions the dataset, fits and predicts the partitions in parallel using all the nodes and cores in your warehouse, and combines the results into a single dataset afterward.
For prerequisites, environment setup, step-by-step guide and instructions, please refer to the QuickStart Guide.