Implement a perceptron in python from scratch and use your implementation to show that the following boolean functions are learnable:

i) the NOT function

ii) the AND function

iii) the OR function

vi) the NAND function.

That is, in each case, train a perceptron model on the appropriate data/labels, depict each boolean function in the appropriate data/label space, and depict the decision boundary showing that each of these functions is learnable by a perceptron.

Finally, train a perceptron model on the XNOR function and depict this function in the appropriate data/label space along with its decision boundary in order to confirm that the function is not learnable by a perceptron.