Data science ideation

Often, coming up with a new idea for a data science project is the most daunting part. You might have numerous doubts. What if I start a project that no one likes? What if my data actually doesn't work out well? What if I can't think of anything? The good news is that if you are creating projects that you actually do care about and would use, then the worst-case scenario is that you have an audience of one! And if you send me ([e-mail])your project, I promise to read it. So that makes it an audience of two at the very least. 

Some examples I have either created or observed in the wild include the following:

• Recording ping-pong games for a semester to determine the best player with an Elo model (http://www.tylerjrichards.com/Ping_pong.html)
• Using natural language processing to determine the quality of Wi-Fi in hostels (https://www.racketracer.com/2015/11/18/practical-natural-language-processing-for-determing-wifi-quality...