For this week, I learned about and used backpropagation, a method of training neural networks.
As a method of learning and testing, I tried to use the backpropagation method to identify if certain random points in the cartesian space were inside the left ‘hollow’ space, right ‘hollow’ space or outside of a lemniscate (a side eight or infinity symbol), which was drawn using the parametric equations.
For this, I generated various random points, used conditions to know where they were in relation to the figure, and then taught the neural network. After this I used other points, different from the ones used for the teaching, but still random, and analised to see if the network correctly identified them as being in the right place.
I also started an exercise that used both backpropagation and hopfield networks, but didn’t finish it due to the amount of patterns necessary – 36 (26 letters and 10 digits).