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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.
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.
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.
A hands-on tour of the Finance Toolkit's Ratios Module in Python, using real output for Apple, Amazon, Meta, and Walmart to compare profitability, liquidity, efficiency, and valuation.
A hands-on walkthrough of exploratory data analysis using R's built-in Iris dataset — aggregate functions, median comparisons, and what the numbers actually tell us about species differentiation.
A practical guide to generating sequences, running simulations, and working with random numbers in R — covering seq(), sample(), runif(), and when each tool is the right one.
Analytics engineer turning fragmented tidbits into confidence: messy data structured, patterns caught early, answers made plain with AI.
Copyright 2026 Christopher A. Rotunno. All Rights Reserved
