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.
-
Jupyter Notebook - Environment
-
Treys Package - This will be used to handle our deck of cards.
-
Make a local copy of this repo.
$ git clone git@github.com:CSCI4850/S18-team4-project.git- 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.
[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
This project is licensed under the MIT License.