If you have a univariate Normal/Gaussian defined by its mean/mu and variance/standard deviation, how can you draw samples from it? Here are the notes: https://raw.githubusercontent.com/Ceyron/machine-learning-and-simulation/main/english/essential_pmf_pdf/univariate_normal_sampling.pdf
Have you ever wondered how packages like SciPy or TensorFlow Probability create samples from a (univariate) Normal distribution? There are quite some ways to do so, but one common way that is also computationally very efficient (on high-performance vector computers) is called the Box-Müller Transform. It takes two uniformly distributed samples and generates two normally distributed ones from them.
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Timestamps:
00:00 Introduction
00:33 Box-Müller Transform
02:10 Python: Standard Normal
04:19 Transform to arbitrary Normal
05:34 Python: Transformation
06:27 Summary
06:39 Outro
