Christopher A. Rotunno
•Mar 11, 2025
CRISP-DM is the closest thing data analytics has to a universal playbook. Here's what the six phases actually mean in practice — and why I keep coming back to it.
Posts tagged with #machine learning
A collection of blog posts about machine learning
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Christopher A. Rotunno
•Mar 11, 2025
Scikit-Learn is the workhorse of applied machine learning in Python. Here's what it does, why it's worth learning deeply, and a practical example to get you started.
Christopher A. Rotunno
•Feb 8, 2025
Both entropy and Gini impurity measure how mixed a node is in a decision tree — but they differ in computation, behavior, and when each makes sense to use.
Christopher A. Rotunno
•Feb 7, 2025
Grid Search exhaustively evaluates every combination in a parameter grid using cross-validation. Here's how it works, when to use it, and a complete implementation with Scikit-Learn.
Christopher A. Rotunno
•Feb 7, 2025
When your parameter space is too large for Grid Search, Randomized Search samples combinations efficiently. Here's how it works and when it outperforms the exhaustive alternative.
Christopher A. Rotunno
•Jul 21, 2023
Regression predicts a number. Classification predicts a category. The difference sounds simple, but it shapes everything — which algorithms to use, how to evaluate results, and what your model actually outputs.