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README.md

Practicum 4: Exploring Data

Learning objectives:

Attribute transformations (normalization, binarization, discretization)
Proximity calculations
Computing summary statistics (mean, median, range, variance, etc.)
Visualization (histograms, scatter plots, box plots)

Exercises

Normalizing values between 0 and 1
Computing the similarity of binary vectors
Discretization
Finding k-nearest neighbors using Eucledian distance
Computing summary statistics on the Iris dataset
Computing summary statistics using numpy
Visualizing Iris data

References