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Deep Learning A-Z™: Artificial Neural Networks (ANN) - The Activation Function

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Kirill Eremenko

Deep Learning A-Z™: Artificial Neural Networks (ANN) - The Activation Function

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© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z Input value 1 Input value 2 Input value m y 2nd step: X1 X2 Xm w1 w2 wm Output value 3rd step
© SuperDataScienceDeep Learning A-Z y 0 1
© SuperDataScienceDeep Learning A-Z 0 y Threshold Function 1
© SuperDataScienceDeep Learning A-Z y 1 0 Sigmoid
© SuperDataScienceDeep Learning A-Z 0 y Rectifier 1
© SuperDataScienceDeep Learning A-Z 0 y 1 -1 Hyperbolic Tangent (tanh)
© SuperDataScienceDeep Learning A-Z Deep sparse rectifier neural networks By Xavier Glorot et al. (2011) Link: http://jmlr.org/proceedings/papers/v15/glorot11a/glorot11a.pdf Additional Reading:
© SuperDataScienceDeep Learning A-Z Input value 1 Input value 2 Input value m y 2nd step: X1 X2 Xm w1 w2 wm Output value 3rd step If threshold activation function: If sigmoid activation function: Assuming the DV is binary (y = 0 or 1)
© SuperDataScienceDeep Learning A-Z y 4 5 6 7 Input value 1 Input value 2 Input value m Output value Input Layer Hidden Layer Output Layer X2 X1 Xm

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