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Use Cases

Machine Learning consists of the following phases.

  • Learning Phase - Analyze huge amounts of data and create a Prediction Model
  • Evaluation Phase - Evaluate model accuracy
  • Prediction Phase - Predict a value according to the input value by using Prediction Model

Use Case in Learning Phase

  • Upload Raw Data - Upload a raw data to Object Storage
  • Parse Raw Data - Parse a raw data to enable MLllib (Apache Spark's scalable machine learning library) to handle it. Users are allowed to parse the parsed data again.
  • Create Prediction Model - Create a Prediction Model by using MLlib

Use Case in Evaluation Phase

  • Create Dataset for Evaluation
  • Evaluate Model Accuracy
  • Recreate Prediciton Model with new datasets or new parameters

Use Case in Prediction Phase

  • Predict - Input any value and retrieve predicted value