Let's create a PRML diagram with Python, Numpy and matplotlib.

The figures described in PRML are mainly created using python, matplotlib, and numpy.

I don't know anything about coding practices, so Please comment if the code is dirty or the calculation efficiency is poor.

Articles that are not linked are the articles that will be listed. I will find some free time and write a lot.

chapter Contents
Chapter 1 Preface Figure 1.4 Polynomial curve fitting
Chapter 1 Preface Figure 1.Bias in maximum likelihood estimation of 15 Gaussian distribution
Chapter 1 Preface Figure 1.17 Bayesian curve fitting
Chapter 1 Preface Exercise 1.4 Non-linear transformation of probability density function
Chapter 2 Probability distribution Figure 2.5 Dirichlet distribution
Chapter 2 Probability distribution Figure 2.7 Gaussian distribution
Chapter 2 Probability distribution Figure 2.Conditional distribution of 9 Gaussian distribution
Chapter 2 Probability distribution Figure 2.Average of 12 Gaussian distribution\muBayesian inference for
Chapter 2 Probability distribution Figure 2.13 Gamma distribution
Chapter 2 Probability distribution Figure 2.14 regular-Gamma distribution
Chapter 2 Probability distribution Figure 2.16 Student's t distribution
Chapter 2 Probability distribution Figure 2.19 von Mises distribution
Chapter 2 Probability distribution Figure 2.25 Kernel density estimation method
Chapter 2 Probability distribution Figure 2.26 K-nearest neighbor method

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