Need Python programmer to update script and remove bug

I have 72 rows python script. For classification works and for regression it has bug. This project and script is connected with BigML code and you need to understand this : [login to view URL] What scripts does ? You have 1 csv file with 1 row of data. Scripts generate 1 row of data with prediction result (for classification +1 or -1 and for regression number). This is it. Very simple script. What you need to know (in theory) ? The Deepnet object you instantiate has a predict method whose first argument should be a dictionary containing each input data you want to predict for. From what I see, your code is creating a Source object with your test data records and using the result as first argument of this predict function. Unfortunately, this won't do what I guess you expect, which is getting a prediction for every row in your test file. The way to do that should be reading your CSV file locally with a standard library, like csv, and looping over the rows like in: import csv with open(test_csv_path) as f: input_data = [login to view URL](f) for test_dict in reader: prediction_info = [login to view URL](input_data) try: # classifications' output contains the prediction and the associated probability and distribution prediction = prediction_info.['prediction'] exception KeyError: # regression predictions are purely a float number prediction = prediction_info This will create predictions locally for every row in you test file. So, the input data for the [login to view URL] method is a dictionary that contains the field values used as input, and this is not what you get from api.create_source call that you used. Note that the output for a classification is a dictionary >>> local_deepnet = Deepnet("deepnet/5a15c8f192527304c20002f2") >>> [login to view URL]({"petal length":1}) {'distribution': [{'category': u'Iris-setosa', 'probability': 0.98134866219833594}, {'category': u'Iris-versicolor', 'probability': 0.014094307515319662}, {'category': u'Iris-virginica', 'probability': 0.0045570302863444431}], 'prediction': u'Iris-setosa', 'probability': 0.98134866219833594} and for a regression is purely a float >>> [login to view URL]({"species":"Iris-setosa"}) 4.5948639935457249 What is the task ? I need to change few lines of code so script will work excellent. I have scripts, PyCharm and test files on Windows server. Please bid on project if you work with BigML before or you really understand BigML API. Price : I will choose freelancer who know this and can work 1-2 hours. Price should be $30 till $50. Thank you! Regards!