For example Stats SE has this:
CrossValidated is for statisticians, data miners, and anyone else doing data analysis or interested in it as a discipline. If you have a question about
- statistical analysis, applied or theoretical
- designing experiments
- collecting data
- data mining
- machine learning
- visualizing data
- probability theory
- mathematical statistics
- statistical and data-driven computing
And here is /help/on-topic at Data Science:
Examples of questions that are likely to be on-topic for Data Science Stack Exchange:
- Given process monitoring data arriving every 10ms, what statistical tool should I use to best characterize a change in the process - mean? a distribution?
- When is it suitable to apply L1 regularization for feature selection?
- I would like to produce a infographic on the 'Brexit' referendum. Given public opinion data across the UK, what are some meaningful techniques to visaualize it in a dashboard?
- When executing an ARIMA model in Spark, what are the pros and cons of using Python instead of R?
- Given Facebook Likes, is there an ML technique to predict age and gender?
If we would like to differentiate from the above sites, we should have our unique section about the topics which people can ask about here.
What description of /help/on-topic page for AI site would you suggest?