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1. Normalized Median Absolute Deviation

   For detecting outliers in non-normally distributed data a common approach is computing the modified z-scores.

   Instead of the standard deviation the median absolute deviation is used as a measure of variability. The metric is defined as the median of the the absolute deviations from the sample median.

   $${\tilde {X}}=\operatorname …

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2. Standard Normal Distribution in a Nutshell

   Given a Gaussian function that depicts the well-known bell-shaped curve.

   $$p(x)=e^{-x^{2}/2},\quad x\in (-\infty ,\infty )$$

   We can compute the integral.

   $$\int _{-\infty }^{\infty }p(x)\,dx=\int _{-\infty }^{\infty }e^{-x^{2}/2}\,dx={\sqrt {2\pi \,}}.$$

   Dividing the Gaussian function by …

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3. An Iterative Workflow for Jupyter Notebook

   Inspecting a data set is usually not a linear process, but involves iterative refinement of the initial assumptions and question. One might have an initial question but after taking a look at the data set realize that it requires multiple preprocessing steps before it can be used to address the …

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4. A Mathematical View on Broadcasting

   The Broadcasting mechanism in NumPy is usually introduced by explaining the relevant rules.

   Another perspective is to look at the topic from a mathematical viewpoint.

   The initial example is the addition of a function and a constant.

   $$f:= \sin{} + C$$

   The authors argue that this is not proper mathematical notation …

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5. Start

   Here I will write about things related to data science.

   For now this site is just a mockup. I will probably use a static site generator and Drafts to write postings.

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