Probability
Last updated
Last updated
This tutorial actually explains why we should use KDE over a Histogram, it explains the cons of histograms and how KDE helps solve some issue that we usually encounter in ‘Sparse’ histograms where the distribution is hard to figure out.
Supposedly a better implementation of KDE than SCIPY
How to use KDE? A tutorial about kernel density and how to use it in python. Has several good graphs and shows use cases.
Video tutorials about Kernel Density:
Non parametric Kernel Regression Estimation
Non parametric Sieve Estimation
Udacity Video Tutorial - pretty good
