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Team Perceptron

This project uses Feed Forward and Convolutional Neural Networks to classify Poker Hands. We are using Poker Hand Data Set obtained from UCL Machine Learning Repository. A detailed walkthrough of the project can be found in the demo/demo.pdf.

Demo and Dependences:

  1. Jupyter Notebook - Environment

  2. Treys Package - This will be used to handle our deck of cards.

  3. Make a local copy of this repo.

    $ git clone [email protected]:CSCI4850/S18-team4-project.git
  1. Walkthrough the demo.ipynb located in the demo directory to learn about our project. The Feed Forward and Convolutional Neural Networks can be found in model directory.

References

[1] M. Shackleford. (2018, March) Poker probabillities - wizard of odds.[Online]. Available: https://wizardofodds.com/games/poker/

[2] M. Moravc´ık, M. Schmid, N. Burch, V. Lisy, D. Morrill, ´N. Bard, T. Davis, K. Waugh, M. Johanson, and M. H.Bowling, “Deepstack: Expert-level artificial intelligence in no-limit poker,” CoRR, vol. abs/1701.01724, 2017. [Online]. Available: http://arxiv.org/abs/1701.01724

[3] S. Jabin, “Poker hand classification,” pp. 269–273, 04 2016.

[4] F. Chollet et al., “Keras,” https://keras.io, 2015.

[5] I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning. MIT Press, 2016, http://www.deeplearningbook.org.

[6] D. Dheeru and E. Karra Taniskidou, “UCI machine learning repository,” 2017. [Online]. Available: http://archive.ics.uci.edu/ml

[7] C. Moffitt, “Guide to encoding categorical values in python.” [Online]. Available: http://pbpython.com/categorical-encoding.html

License

This project is licensed under the MIT License.