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 |
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 |
Recommended Posts