PRML in Julia These are PRML sample programs written in Julia. Contents 1. Introduction 1-1. Polynomial Curve Fitting 1-2. Regularization 1-3. Bayesian Curve Fitting 1-4. Model Evaluation 2. Probability Distributions 3. Linear Models for Regression 4. Linear Models for Classification 5. Neural Networks 6. Kernel Methods 7. Sparse Kernel Machines 8. Graphical Models 9. Mixture Models and EM 10. Approximate Inference 11. Sampling Methods 12. Continuous Latent Variables 13. Sequential Data 14. Combining Models