small change in 03_ml_basics_simple_neural_network.ipynb
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@ -23,6 +23,7 @@
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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@ -76,7 +77,7 @@
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"\n",
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"Note, that it is assumed that the activation function is a sigmoid with the derivative\n",
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"\n",
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"$$ \\sigma(x) * (1 - \\sigma(x)) $$\n",
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"$$ \\sigma(x) \\cdot (1 - \\sigma(x)) $$\n",
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"\n",
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"Applying the chain rule further, we obtain the gradient for the weights from the input layer to the hidden layer: \n",
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"\n",
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