Monitoring, Evaluating, and More

“Focus on how the end-user customers perceive the impact of your innovation – rather than on how you, the innovators, perceive it.” — Thomas A. Edison

Congratulations, you’ve made it to the final chapter! We’ve come a long way, yet there is still more to explore in Databricks. As we wrap up, we will take another look at Lakehouse Monitoring. We’ll focus on monitoring model inference data. After all the work you’ve put in to build a robust model and push it into production, it’s essential to share the learnings, predictions, and other outcomes with a broad audience. Sharing results with dashboards is very common. We will cover how to create visualizations for dashboards in both the new Lakeview dashboards and the standard Databricks SQL dashboards. Deployed models can be shared via a web application. Therefore, we will not only introduce Hugging Face Spaces but also deploy the RAG chatbot...