tall and wide data

Architects Research Society

Nov 21, 2016 · Artificial Intelligence

Data Science Q&A: Overfitting, Experimental Design, Tall/Wide Data, Chart Junk, Outliers, Extreme Value Theory, Recommendation Engines, and Visualization

This article presents a series of data‑science questions and expert answers covering overfitting, experimental design for user behavior, the distinction between tall and wide data, detecting chart junk, outlier detection methods, extreme‑value theory for rare events, recommendation‑engine fundamentals, and techniques for visualizing high‑dimensional data.