Considerations for ML model iterations
Numerous books have been written about ML and reasons that ML models perform well or poorly, including books from Packt Publishing. The purpose of this book is to help you learn Power BI so that you can explore the FAA Wildlife Strike data, analyze that data, and then create SaaS ML models. At this point in this book, you are at a crossroads. Do you continue to iterate these ML models in the SaaS tool? Have you demonstrated enough value to hand an ML model project over to a data science team who will improve upon the model using Azure ML or advanced tools? Or do you go back to your stakeholders, report your findings, and ask for guidance on the next steps? The following diagram shows a few options for the next steps you could consider:
Figure 10.1 – Possible next steps for your Power BI ML models
Rather than diving into the technicalities of ML theory, you will focus on a few possible causes of inaccuracy that...
