This project is a demonstration of a basic implementation of a Perceptron Neural Network in Python. It involves training the network using random weights and bias, followed by testing it with specific input.
The Perceptron is trained using a dataset, adjusting weights and bias to match the provided inputs. Once trained, it can predict outputs based on new input values.
To test the trained Perceptron, modify the entrada_teste variable in the ia-perceptron-de-resenblatt.py script with new values and execute the script again.