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OutlierStudentDetection

Simple GUI that interactively demonstrates a Proof of Concept (PoC) Machine Learning ETL pipeline for outlier detection

Screenshot

  • Extract: reads data from a database (several csv files in this case).
  • Transform: converts the extracted data by using a simple Machine Learning outlier detector model; combines the data with an extra feature column linking each record to its original source (the original csv file).
  • Load: writes the data into a target database (a single csv file in this case).

Install:

 $ git clone https://github.com/juanmcloaiza/OutlierStudentDetection.git
 $ cd OutlierStudentDetection
 $ python3 -m venv ./localEnv
 $ source ./localEnv/bin/activate
 $ pip install --upgrade pip
 $ pip install -r requirements.txt

Run:

 $ python poc.py