Practical AI And Machine Learning Experiments

Lessons:

In Power BI, we connect to a machine learning model where we can adjust two parameters of Average discount (applied across all products) and Price elasticity.

By changing these two parameters you will see the other visualizations’ measures beginning with “new” updating. While these are straightforward relationships, what if analysis will allow the report’s users to develop an intuitive understanding for the underlying sensitivities.

Especially when there is little prior knowledge about the data and the variation in inputs, what if analysis explains the relationships between the inputs and relevant KPIs so they are well understood and modelled.

Lab :

• Azure ML Real Time Scoring
• What if Analysis

After completing this module, students will be able to:

• Use what if analysis with Azure Machine Learning in your Power BI report to develop an intuitive understanding for the underlying sensitives in your data

Lessons:

You will configure a real time Power BI tile to visualize real time weather data. For the Power BI tile, you will select the axis as the time series, and then display whichever weather measure you want as the values on the chart. Once setup with an automatic backend feeder from Microsoft Flow, you should now be all set to see real time weather, and see data appear on your dashboard tile in real-time.

Lab:

• Create a real time Power BI tile
• Access the weather API
• Use Microsoft Flow as the AI engine room

After completing this module, students will be able to:

• In just a few minutes you have been able to set a new streaming data source for Power BI without writing a single line of code.

Lessons:

You will configure a real time Power BI tile to visualize real time sentiment analysis.   For the Power BI tile, you will select the axis as the time series, and then display whichever sentiment measure you want as the values on the chart. Once setup with an automatic backend feeder from Microsoft Flow, you should now be all set to see real time sentiment scores, and see data appear on your dashboard tile in real-time.

Lab:

• Create a real time Power BI tile
• Access the Text Analytics API for sentiment analysis
• Use Microsoft Flow as the AI engine room

After completing this module, students will be able to:

• In just a few minutes you have been able to set a new streaming data source for Power BI without writing a single line of code.

Lessons:

This course will show you how to do insert data into a Power BI Dataset from Microsoft Flow. You will register a Power BI Application, create a custom API in flow, automate the flow, and write to a Power BI dataset. 

Lab:

• Register an Application for Power BI
• Configure Flow for a custom API
• Use Microsoft Flow as the AI engine room

After completing this module, students will be able to:

• In just a few minutes you will be able to insert a new dataset in Power BI without writing a single line of code.