Feedback from Seung

[kr900910]

@mballschmiede

I think your idea is about providing affordable but luxurious micro-apartments for those who live in cities.

• What should be kept: Dave, Susan, Betty, and Juan examples clearly demonstrate potential clients for your solution. This alone can convince readers how relevant your solution is to modern urban population.

• What could be cut: I think you can cut this line "Conversely, common areas will be spacious, plenty, and capable of tailoring to every need" since you want "optimizing building layouts" which can't satisfy everyone's need.

• What could be rearranged: I think it will be more effective for readers to dive into the problem if you move Dave, Susan, Betty, and Juan examples to the beginning. Also, it might be a good idea to "include a research question at the beginning of your middle" to make sure readers can clearly understand how your solution will be implemented.

• What could be added: I think it will be interesting if you can explain more about how data science can solve the problem. What would be alternative data sources you can use to plan your buildings? Can a machine learning method like clustering help you optimize building layouts given large amount of data about potential residents?

Overall, this is an interesting topic with significant potential impact on daily lives of many city-dwellers.

[mballschmiede]

Thanks for the feedback, Seung. I edited the "conversely" line to make it less extreme. I also tried to add some more concrete DS examples regarding implementation.