Multimodal deep learning models continue improving rapidly, but creating real-world applications that effectively leverage multiple data types remains challenging. This hands-on tutorial covers model selection, embedding storage, fine-tuning, and production deployment through two practical examples: a historical manuscript search system and flood forecasting with satellite imagery and time series data.