[User Story] A novice users wants to know what AI (DataFactory) can do for them #17
Description
A production engineer that has downloaded logging information from his machines want to know what he can do with the data using AI. After reading the provided documentation he understand that the tool might be useful for him.
A web shop owner who has customer base data, purchase information and click statistics for different product pages wants to understand what type of recommender system he can build with the data. After reading the provided documentation he understand that the tool might be useful for him.
A measurement device manufacturer has problems calibrating his devices in the field and has collected data with ground truth wants to understand what he can do using AI. After reading the provided documentation he understand that the tool might be useful for him.
Methods:
- A notebook called “??” that describes all the tasks that DataFactory can deal with and include links for each task demonstration (regression, rule extraction (classification), feature importance, causal inference)
- Before linking to the demonstration notebook, in the source notebook should introduce the function with a small example
Acceptance criterion:
- The Notebook should describe all the tasks in the datafactory and the explanation of the tasks should be clear enough for the beginner.
- Each function should have a corresponding demonstration notebook and it’s better to use the industrial data set as example in the notebook. and if possible, use the same dataset in different notebooks.
- All the demonstration notebooks should keep the same structure and be written in German.
- Before linking to the demonstration notebook, in the source notebook should introduce the function with a small example.
- looking for beginners and summarize feedback from them (Pfinder, MUEKO, maybe former clients, or Rainer’s industrial students), decide whether accept of not according to the feedbacks.