Tag: xgboost
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Stop Asking the LLM to Do the ML’s Job
Before 2023, if you wanted a model to predict something, you had to build one. Gather data, pick features, choose an algorithm, train it, validate it, deploy it. That’s real work, and it’s work most business teams couldn’t do without a data scientist. Then LLMs showed up and could apparently do “AI stuff” without any…
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Classification Models: Pick the Right Tool
The Reality of Algorithm Selection Here’s the thing nobody tells you when you’re starting out: the algorithm usually matters less than you think. I’ve seen data scientists spend weeks optimizing model selection when their real problem was dirty data or bad features. But—and this is important—sometimes the algorithm choice makes a massive difference. Knowing when…