Can you design and train an ML algorithm for this Pandas Sex Dataset? An ML Choose Your Own Adventure!

You have just been tasked with a highly lucrative government contract after you replied to some lady on LinkdIn who was cold messaging anyone who had “Machine Learning” listed as experience on their profile. The offer requested competency in supervised, unsupervised and reinforcement learning on some Pandas datasets, so it was too intriguing not to respond. You accepted with no further information because the job pays well and you are currently in between jobs. You find yourself in listening to a three-star general in a briefing room at the pentagon. He begins showing you a presentation filled with so many buzzwords and mislabeled graphics you have no idea what he’s talking to. When they started talking about contracts, schedules and where the money comes from, you struggled to fight the sleepiness. At the end of the presentation, it looks like they’re using some AI that’s giving them erroneous advice and that you will be provided with data to fix or replace that AI as the previous engineer had quit his job to go work at some big tech firm and won’t return any of their calls or emails. You first fight the urge to tell them that it’s probably an ML algorithm not an AI only to realize it doesn’t matter. What do ya do?

Ask what the AI is supposed to do?

Look at the data, whatever it is, you’ll be able to figure it out. You might have dozed off during the meeting and missed it or you are about to be treated to a dozen more hidden backup slides.

Just get into the Algorithm, data is Data!

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.

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