Core ML Concepts · beginner · concept 17 of 176
Exploratory Data Analysis (EDA)
The discipline of looking at the data before modeling it: distributions, missing values, outliers, correlations, and the weird rows that reveal how the data was actually collected. An hour of EDA routinely saves a week of debugging a model trained on data you did not understand.
Key terms
DistributionsOutliersMissing valuesCorrelation matrixData profiling
Where you meet it in the real world
The first day of every real ML project; where data leakage and label problems get caught early
Videos
▶ Exploratory Data Analysis ↗
IBM Technology · YouTube
Guides and articles
Courses, papers, and more