Jesus A. Gonzalez
August 10, 2019
A Neural Network is a set of interconnected input and output units in which each connection has an associated weight
During the learning phase, the weights are adjusted in such a way that the network is able to correctly predict the class of new examples
\[o(x_1, \dots, x_n) = \begin{cases} 1 & \text{ if } \sum\limits_{i=0}^{n}w_ix_i > 0 \\ -1 & \text{otherwise} \end{cases}\]
\(J(W_1, b_1, W_2, b_2) = \sum\limits_{i=1}^{m} (\tilde x^{(i)} - x^{(i)})^2\)
\(= \sum\limits_{i=1}^{m} (W_2z^{(i)} + b_2 - x^{(i)})^2\)
\(= \sum\limits_{i=1}^{m} (W_2(W_1 x^{(i)} + b_1) + b_2 - x^{(i)})^2\)