Week 6: density estimation¶
Density estimation in data science is the process of reconstructing the underlying probability density function (PDF) of a dataset to understand its distribution. Common methods include simple histograms and more advanced techniques like Kernel Density Estimation (KDE) and Gaussian Mixture Models (GMMs). This estimation is used for analyzing data properties, visualization, classification, and anomaly detection
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