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Neural networks (2)

  • What we refer to as Neural Networks in the course are mostly Artificial Neural Networks (ANN).

  • ANN are approximation of biological neural networks and are built of physical devices, or simulated on computers.

  • ANN are parallel computational entities that consist of multiple simple processing units that are connected in specific ways in order to perform the desired tasks.

  • Remember: ANN are computationally primitive approximations of the real biological brains .

  • Application examples : e.g., handwriting recognition, time series prediction, kernel machines (support vector machines, data compression, financial predication, speech recognition, computer vision, protein structures

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