Implementing Logic Gates using Neural Networks (Part 2)
<p>Hello everyone!! Before starting with part 2 of implementing logic gates using Neural networks, you would want to go through <a href="https://medium.com/@vedantk.0704/implementing-logic-gates-using-neural-networks-part-1-f8c0d3c48332" rel="noopener">part1</a> first.</p>
<p>From part 1, we had figured out that we have two input neurons or x vector having values as x1 and x2 and 1 being the bias value. The input values, i.e., x1, x2, and 1 is multiplied with their respective weight matrix that is W1, W2, and W0. The corresponding value is then fed to the summation neuron where we have the summed value which is</p>
<p><a href="https://towardsdatascience.com/implementing-logic-gates-using-neural-networks-part-2-b284cc159fce"><strong>Click Here</strong></a></p>