PRML ( Pattern Recognition And Machine Learning )

A figure-wise implementation of PRML

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About The Project

Inspired from the opensource implementation ( github ) of Reinforcement Learning-An introduction,a well known book by Rich Sutton and Andrew Barto, I started the figure wise implementation of PRML - Patten recognition and Machine Learning.

There are several implementations of the book already implemented by the great community ( see reference section ), however none of them uses the figure-wise approach in my knowledge.

The aim of the projects are

• chapter wise and figure wise implementation of the PRML book.
• All figures have standalone implementation, requiring as fewer libraries and inter dependencies as possible.

Built With

Getting Started

Please clone or fork to get started.

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

Please see the chapter you can contribute to. Please consider implementing single chapter in a folder and under either single notebook ( in case no. of figures in chapter are less ) or over multiple notebooks.

1. Read the aim of project for guidelines.
2. Fork the Project
3. Create your Feature Branch (git checkout -b feature/AmazingFeature)
4. Commit your Changes (git commit -m 'Add some AmazingFeature')
5. Push to the Branch (git push origin feature/AmazingFeature)
6. Open a Pull Request

References

1. Implementation of Reinforcement-learning An Introduction
2. Referenced implementation of PRML by ctgk
3. Referenced implementation of PRML by gerdm

License

Distributed under the MIT License. See LICENSE for more information.

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