examples = [([0,0],0),([0,1],0),([1,0],0),([1,1],1)]
weights, bias = [0.0,0.0], 0.0
for epoch in range(20):
    errors = 0
    for x,target in examples:
        predicted = int(sum(w*v for w,v in zip(weights,x,strict=True))+bias >= 0)
        error = target-predicted
        if error:
            weights = [w+error*v for w,v in zip(weights,x,strict=True)]
            bias += error
            errors += 1
    if errors == 0:
        break
print([int(sum(w*v for w,v in zip(weights,x,strict=True))+bias >= 0) for x,_ in examples])