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116 bytes added ,  16:52, 10 October 2017
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The code contains two parts: Data Preprocessing and Model Training/Prediction.
* Data Preprocessing (preprocessing.py) : this is where you transfer a text based "XXX.txt" input file into a numerical value based pickle file that the later part of the code can understand and use for training and prediction.  * Step 1 : modify the target file name in "main()"
* Step 1 : modify the target file name in main()
# don't add ".txt" extension
file_name = 'ThicketDefCodingTestProcessed'
 * Step 2 : specify the expected columns of your target file  # expected number of columns, in case we have "None" in the table expected_columns = 5 
The second part of the code is where the deep neural network is. It will load in the pickle file you generated in the previous step and train the neural network. At the end, the well trained neural network will predict on your testing examples and print the accuracy. To run this part:
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