This session we will learn about Power BI ML and OpenAI as follows:
Preparing and Ingesting Data with Power Query consists of data transformation and modeling to prep data for both a Power BI dataset and queries that will be used to build ML models.
Exploring Data Using Power BI and Creating a Semantic Mode o discover features for ML models.
Model Data for Machine Learning in Power BI will explore the data using Power BI to discover potential features that can be used to build ML models.
Discovering Features Using Analytics and AI Visuals leverages Power BI as an analytics and data visualization tool to discover new features for the ML queries.
Discovering New Features Using R and Python Visuals, discovers additional features for the ML queries using the R and Python visuals in Power BI
Building Machine Learning Models with Power BI, builds ML models in Power BI. The ML queries designed in the previous chapters are used to build three ML models for binary classification, general classification, and regression predictions.
Evaluating Trained and Tested ML Models, reviews the three ML models that were built in Power BI. The testing results are reviewed and explained in the context of predictive capabilities.
Use Cases for OpenAI, plans for the use of OpenAI with the project and workshop.
This is a maximum demo session with minimum theory! My previous lecture is Self AI in Power BI Desktop Using R, Python and ChatGPT