Book Content
chapters • 10h16m total length
1. Requirements, Data Modeling, and Planning
2. Preparing and Ingesting Data with Power Query
3. Exploring Data using Power BI and Creating a Semantic Model
4. Model Data for Machine Learning in Power BI
5. Discovering Features Using Analytics and AI Visuals
6. Discovering New Features Using R and Python visuals
7. Deploying Data Ingestion and Transformation Components to the Power BI Cloud Service
8. Building Machine Learning Models with Power BI
9. Evaluating Trained and Tested ML Models
10. Iterating Power BI ML Models
11. Applying Power BI ML Models
12. Use Cases for OpenAI
13. Using OpenAI and Azure OpenAI in Power BI Dataflows
14. Project Review and Looking Forward
