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Intelligent Systems

// TECHNOLOGY INDEX

Artificial Intelligence For Your Business

The main goal in supervised learning is to learn a model from labeled training data that allows us to make predictions about unseen or future data. Examples:

  • Speech Recognition
  • Image Recognition
  • Predictive Maintenance

Unsupervised learning is a type of machine learning algorithm used to draw inferences from datasets without human intervention, in contrast to supervised learning where labels are provided along with the data.

Reinforcement learning is a type of machine learning technique where a computer agent learns to perform a task through repeated trial and error interactions with a dynamic environment. Examples:

  • Robotics
  • Scheduling
  • Calibration

Deep learning allows machines to solve complex problems even when using a data set that is very diverse, unstructured and inter-connected. Examples:

  • Automated Driving
  • Medical Research
  • Industrial Automation

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