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Machine Learning

The following section covers four machine learning steps,

  • Classification Model Builder
  • Prediction
  • Build Model For Intent Classification And Entity Extraction
  • Intent Classification And Entity Extraction

The first two Machine Learning plugin steps namely ‘Classification Model Builder’ and ‘Prediction’ let you build a classification model and then use this model for prediction. These plugin steps solve classification type problem where value to be predicted takes a set of discrete values as opposed to continues values (when the value being predicted is a continuous variable, such problem is called as regression problem). Below are a few examples where these steps can be used,

  • Predict support group based on issue description
  • Predict customer churn based on past customer data
  • Predict occupational class of the person being insured based on various attributes of the person
  • Predict customers from your customer list which are likely to show interest in your new promotions

The last two Machine Learning plugin steps namely ‘Build Model for Intent Classification’ and Entity Extraction’ and ‘Intent Classification and Entity Extraction’ let you build a model for Intent Classification and Entity Extraction and then use this model for Intent Classification and Entity Extraction. Identification of Intent and entity has a huge variety of use cases in industry wherever there is a need to understand the intention behind the utterances from users and automate certain processes.

Recommendation: For more accurate execution results, we recommend using Python version 3.8.10 and above.

Prerequisites:

  • Use a system which has a minimum of 8GB RAM.
  • AE Python setup (Python setup 3.6.1 or 3.8.10)

Note: Support is available for both, Python 3.6.1 and Python 3.8.10. However, you cannot use both versions simultaneously. For example, if you are currently using Python version 3.6.1 and want to use 3.8.10, then first close the current Process Studio instance, update the Python setup to version 3.8.10 and restart the Process Studio.

Local AE Python setup steps:

  1. Download the AutomationEdge’s Python distribution from the link provided in the mail.
  2. Close Process Studio instances and/or Agents where Machine Learning plugin is to be used.
  3. Create a folder by the name ‘python’ – case sensitive i.e., all letters in small case – in your <Process Studio root> and/or <Agent root> folders*.
  4. Unzip the downloaded file in the following location: <Process Studio root>/python/ and/or <Agent root>/python/
  5. Post completion of step three, your folder structure should now look like: <Process Studio root>/python/AE_Python<Version> For example, D:/process-studio/python/AE_Python3.8 <Agent root>/python/AE_Python<Version> For example, D:/ae-agent/python/AE_Python3.8
  6. Start Process Studio instances and/or Agents wherever this change has been made. If you skipped Step 2, just restart the instances.

* <Process Studio Root> is the main Process Studio folder once you have unzipped Process Studio <by default, the folder name is process-studio> and similarly <Agent home> is main agent folder after unzipping <named ae-agent>

  • Get Python Setup zip(Python38.zip) file from AutomationEdge
  • Extract Python38
  • Add the following filepaths to the PATH Environment Variable as below:
    • <path_till_python_directory>\Python38;<path_till_python_directory>\Python38\Scripts;

Note: Perform Step 4 only if you are setting up Python 3.6.1, else proceed with Step 5.

  • Create symbolic link for spacy en_core_web_sm model:
    • Traverse to below path: ..\Python38\lib\site-packages\spacy\data Delete folder/directory viz., en.
    • On Command line execute the following command to create symbolic link: python -m spacy link en_core_web_sm en --force
  • For older generation Pentium machines hardware specific Tensorflow libraries
  • Microsoft Visual Studio C++ distribution specific to Windows OS
  • Steps viz., Intent Entity Model Builder and Intent Entity Prediction use Tensorflow libraries. For compilation of these Tensorflow libraries, the processing machine’s processor requires, AVX –Instruction Set Extension support. You may refer your Processor manual to check for AVX support. (for e.g. in case of intel processor the details can be obtained from the following URL- https://ark.intel.com/content/www/us/en/ark.html#@Processors)
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