Intelligent automation is the sweet spot between robotic process automation (RPA) and the broad categorization of artificial intelligence (AI) to mimic cognitive decision making in task automation. In this second part of our 2 part series on intelligent automation, we'll be using the Machine Learning Classifier tool discuss in part one to assist in training a machine learning model, and using that model from within our bot to appropriately classify IT helpdesk tickets. Note: if you haven't checked out part I of our series, check that out here to get a background on the use case introduced as well as the tool we'll be using in this session.
If you want to follow along in the AAillustrates session, you'll need the following resources:
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An Enterprise/Community A2019 Account
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You can use Automation Anywhere Enterprise A2019 or Automation Anywhere Community Edition.
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If you don't yet have an account, be sure to sign up here so you can get started in setting up your environment and getting your bot agent connected.
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The ML Classifier App
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This application was introduced in the first session. Download the full source code from GitHub (which includes the pre-built app) so you can follow along with part 2.
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If you aren't familiar with downloading from GitHub...
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Click the green Code button and select the option that says Download ZIP
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This will download the entire project to your downloads directory.
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Unzip the project. In it, you will find two .tsv files, a readme.md file, and a zip called MachineLearningClassify.zip
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Unzip the MachineLeaningClassify.zip
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The path to the executable that we use in the session is MachineLearningClassifyMachineLearningClassifyinDebugMachineLearningClassify.exe
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The Test/Train Datasets
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Download the IT Helpdesk train and test datasets from the Automation Anywhere GitHub page
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If you aren't familiar with download from GitHub, follow the instructions above to download both tsv files.
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That's it! You're ready to get started following along in the #AAIllustrates Intelligent Automation Pt II full bot build