Machine Learning, Clustering, Python, Gaussian Mixture Model, Unsupervised Learning.
given the model parameters 𝜋𝑘 𝜇𝑘 and 𝜎𝑘. The second step is known as the maximization step or 𝑀 step, which consists of maximizing the expectations calculated in the E step with respect to the model parameters. This step consists of updating the values 𝜋𝑘, 𝜇𝑘, and 𝜎𝑘. The entire iterative process