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Sin título

mark fabian Inglés 16 fichas

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  1. 1Zfunction for linear combination of inputs/weights/bias
  2. 2sigmoidfunction that converts Z into 0,1
    tanh into -1,0,1
    Relu into 0,Z
    Leaqky relu into 0.01,Z
  3. 3tanh/relu/leaky relulike sigmoid function, it converts Z into -1,0,1.
  4. 4RNNrecurrent neural network that is based on the order of sequence of data - used on data like speech, or music
  5. 5weightparameter that represents strength of one neuron to another
  6. 6cost function/loss function/objective functionmeasures difference between predicted output and true output
  7. 7back propagationalgorithm used to minimize cost function CALCULATES gradients (partial derivatives). It is a step in optimization.
  8. 8n^[l]subscript_(h)​n = neuron
    l = layer
    h = specific neuron in lth layer
  9. 9Xinput data matrix
  10. 10gradient descentalgorithm used to minimize cost function, USES gradients (partial derivates)
  11. 11WWeight
  12. 12bBias
  13. 13aa=activation_function(weighted_sum+bias)
  14. 14y-hatPredicted output
  15. 15Pprobability (function given y)
  16. 16initializationwhat you set the parameters (weights and bias) to before training.

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Fichas sobre Sin título, creado por mark fabian el 01/02/2024.
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mark fabian
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