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fix a typo #426

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2 changes: 1 addition & 1 deletion docs/notebooks/nonlinear_gaussian_ssm/ekf_mlp.ipynb
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Expand Up @@ -154,7 +154,7 @@
"source": [
"## Neural network\n",
"\n",
"We aim to approximate the true data generating function, $f(x)$, with a parametric approximation, $h(\\theta, x)$, where $\\theta$ are the parameters and $x$ are the inputs. We use a simple feedforward neural network — a.k.a. multi-layer perceptron (MLP) — with sigmoidal noinlinearities. Here, $\\theta$ corresponds to the flattened vector of all the weights from all the layers of the model. "
"We aim to approximate the true data generating function, $f(x)$, with a parametric approximation, $h(\\theta, x)$, where $\\theta$ are the parameters and $x$ are the inputs. We use a simple feedforward neural network — a.k.a. multi-layer perceptron (MLP) — with sigmoidal nonlinearities. Here, $\\theta$ corresponds to the flattened vector of all the weights from all the layers of the model. "
]
},
{
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