machine learning
Machine Learning, Math
Mastering the Softmax Function: Understanding its Derivative with a Step-by-Step Example
\title{Mastering the Softmax Function: Understanding its Derivative with a Step-by-Step Example} \maketitle This article focuses on obtaining the derivative of the softmax function by means of a simple example. It
Maximum Likelihood Estimation
The method of maximum likelihood estimation allows to estimate point parameters for a given distribution underlying some observed data. Let’s look at an example to understand what this means:Imagine you
How to create a random variable with a Beta distribution from scratch, using only Uniform random variables
You can use software, like scipy.stats.beta if you want to sample from a Beta distribution. But you can also create a Beta distribution yourself — from scratch. The only thing you need
Understanding the Probability Density Function of the Normal Distribution
A random variable $Z$ is said to have the standard normal distribution, if its probability density function (pdf) is as follows: \[\begin{equation}f_Z(z)=\frac{1}{\sqrt{2\pi}} * \exp(\frac{-z^2}{2}), \quad -\infty<z<\infty\end{equation} \tag{1}\label{eq:eq1} \] This formula