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 β€˜Sparse’ histograms where the distribution is hard to figure out.
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:
  1. 1.
    ​KDE ​
  2. 2.
    Non parametric Kernel Regression Estimation​
  3. 3.
    Non parametric Sieve Estimation​
​Udacity Video Tutorial - pretty good
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Kernel Density Estimation