Small fixes

src/year1/image-processing-and-computer-vision/module2/sections/_classification.tex

@@ -332,7 +332,7 @@ The prediction is obtained as the index of the maximum score.
         \]
         where:
             \begin{itemize}
-                \item $\matr{\theta} = (W_1 \in \mathbb{R}^{h \times i}, b_1 \in \mathbb{R}^{h}, W_2 \in \mathbb{R}^{c \times h}, b_2 \in \mathbb{R}^{c})$
+                \item $\matr{\theta} = (\matr{W}_1 \in \mathbb{R}^{h \times i}, \vec{b}_1 \in \mathbb{R}^{h}, \matr{W}_2 \in \mathbb{R}^{c \times h}, \vec{b}_2 \in \mathbb{R}^{c})$
                     are the parameters of the linear transformations with an inner representation of size $h$.
                 \item $\phi$ is an activation function.
                 \item $\vec{h}$ and $\vec{s}$ are activations.