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by oh-kumudo
2907 days ago
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The title is often true, but it doesn't mean too much or anything. And the same argument is brought up again and again in the past as well. What OP suggests, the so called SQL, is basically a heuristic based system. When done probably and carefully, it could of course work very well, and is indeed often used as baseline model to bootstrap a ML system. However, eventually the rule-based system will hit the wall, and ML be the savior of the day to push the metric further for a margin of 20-30%. So yes, when you are small and has little data, ML is irrelevant. But same thing could be said to too many things in software industry, you probably won't need Docker/Big Data/Fancy JS as well, if you are building a small scale online store. Choose wisely your tech stack based on your problem, but the title is needlessly sensationalized. |
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For things like figuring out who your biggest customers are, SQL probably is the right tool for the job. Whale-spotting probably gives a decent bang per buck, and isn't particularly complex.
But when he gets onto recommendations, it starts to look like it's the author who's attached to the wrong tool for the job. His example of recommending sunglasses to people who buy sunglasses is terribly blunt. If someone in my locale, who doesn't regularly buy sunglasses, buys sunglasses; they're probably going on vacation - there's not much sun at home for them. Surely there's a whole raft of things someone excited for their summer holidays would impulse-buy, but the sunglasses they just bought are no longer on the list.
If ML can match them up with with a "going on summer holidays" demographic, and BI wants to sell them the only thing we know they no longer need, it's no longer making a strong case for blunt instruments.