[PDF] application of supervised learning

Real-Life Applications of Supervised Learning
  • Risk Assessment. Supervised learning is used to assess the risk in financial services or insurance domains in order to minimize the risk portfolio of the companies.
  • Image Classification.
  • Fraud Detection.
  • Visual Recognition.
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  • What are the applications of supervised and unsupervised learning?

    Supervised Learning is used in areas of risk assessment, image classification, fraud detection, visual recognition, etc.
    In Unsupervised Learning, the algorithm is trained using data that is unlabeled.
    The machine tries to identify the hidden patterns and give the response.

  • What are the applications of supervised and unsupervised learning?

    Applications: Supervised learning models are ideal for spam detection, sentiment analysis, weather forecasting and pricing predictions, among other things.
    In contrast, unsupervised learning is a great fit for anomaly detection, recommendation engines, customer personas and medical imaging.

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