[pwang]

This is absolutely hilarious. One of the things I talk about in my presentations is that the hardest part of "data analytics" and especially "advanced visualization" is that it's hard to know when you're sucking. It's actually pretty easy to come up with some basic interesting things, but then what do you benchmark against? If you don't do the hard work to evaluate significance, you can start convincing yourself that you're more insightful than you actually are.

What the business people don't appreciate is that the ML models don't know they're looking at DVD players and TV stands. They just know that vector elements 27 and 291 have the strongest correlation. It takes a human in the loop to say, "item 291 is technically just TV Stands, but we've done dimensional reduction to pool TVs, TV Stands, and Projectors all into cluster 14, which then correlates to cluster 12, consisting of DVD players and Xboxes".