ctgk/PRML
PRML algorithms implemented in Python
| repo name | ctgk/PRML |
| repo link | https://github.com/ctgk/PRML |
| homepage | |
| language | Jupyter Notebook |
| size (curr.) | 23203 kB |
| stars (curr.) | 7414 |
| created | 2017-02-05 |
| license | MIT License |
PRML
Python codes implementing algorithms described in Bishop’s book “Pattern Recognition and Machine Learning”
Required Packages
- python 3
- numpy
- scipy
- jupyter (optional: to run jupyter notebooks)
- matplotlib (optional: to plot results in the notebooks)
- sklearn (optional: to fetch data)
Notebooks
- ch1. Introduction
- ch2. Probability Distributions
- ch3. Linear Models for Regression
- ch4. Linear Models for Classification
- ch5. Neural Networks
- ch6. Kernel Methods
- ch7. Sparse Kernel Machines
- ch9. Mixture Models and EM
- ch10. Approximate Inference
- ch11. Sampling Methods
- ch12. Continuous Latent Variables
