That was a good idea, that data was nasty grimey, tons of nulls everywhere, there’s no way it would have worked on any of your supervised ML algorithms. At least, it wouldn’t have worked very well. The data might have said how many cubs a panda couple would have had, but it didn’t completely capture the emotional compatibility required to have a lot of kids. Alright, the data’s clean now, what do you do?
You Clean the Data! Nice
Published by B McGraw
B McGraw has lived a long and successful professional life as a software developer and researcher. After completing his BS in spaghetti coding at the department of the dark arts at Cranberry Lemon in 2005 he wasted no time in getting a masters in debugging by print statement in 2008 and obtaining his PhD with research in screwing up repos on Github in 2014. That's when he could finally get paid. In 2018 B McGraw finally made the big step of defaulting on his student loans and began advancing his career by adding his name on other people's research papers after finding one grammatical mistake in the Peer Review process. View more posts