Update README.md

README.md

@@ -6,6 +6,9 @@ This is the companion repository for our paper titled "Transfer learning for tim
 
 ## Source code
 The software is developed using Python 3.5. We trained the models on a cluster of more than 60 GPUs. You will need the [UCR archive](https://www.cs.ucr.edu/~eamonn/time_series_data/) to re-run the experiments of the paper. 
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+If you encouter any problems with cython, you can re-generate the "c" files using the [build-cython.sh] [[TDO ADD LINK]] script. 
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 ### Pre-trained and fine-tuned models
 You can download from the companion [web page](http://germain-forestier.info/bigdata2018/) all pre-trained and fine-tuned models you would need to re-produce the experiments. 
 Feel free to fine-tune on your own datasets !!! 
@@ -21,6 +24,7 @@ All python packages needed are listed in [pip-requirements.txt] [[TDO ADD LINK]]
 * [tensorflow-gpu](https://www.tensorflow.org/)  
 * [keras](https://keras.io/)  
 * [h5py](http://docs.h5py.org/en/latest/build.html)
+* [cython](https://cython.org/)
 
 ## Results
 You can download [here](https://github.com/hfawaz/bigdata18/blob/master/results/df_transfer.csv) the accuracy variation matrix which corresponds to the raw results of the transfer matrix in the paper.