This solution generates upsell and cross-sell recommendations to increase sales for the Tasty Bytes business. This involves:
- Extracting features from customer, menu, and purchase history.
- Preprocessing data using the Snowpark ML library.
- Training a PyTorch DLRM model with distributed processing on GPUs.
- Registering the model and deploying it to a container runtime environment.
- Running predictions and visualizing recommendations on Streamlit.
- Displaying personalized menu item recommendations along with purchase history in a Streamlit app.
For prerequisites, environment setup, step-by-step guide and instructions, please refer to the QuickStart Guide.