A bit late now to answer, but in case anyone else stumbles on it: for that same neural net example tutorial, it turned out I had to wrap the 3 zip calls in the mnist_loader with a list(zip(...)) construct:

training_data = list(zip(training_inputs, training_results))
(...)
validation_data = list(zip(validation_inputs, va_d[1]))
(...)
test_data = list(zip(test_inputs, te_d[1]))

And then it worked.

Force the zip() to evaluate.

foo = list(zip(...))

Some Info

This is because in the Python 3.x, zip returns a generator object. This object is not a list (it's better) but it behaves like one. You can try iterating through it like this:

for i in zip([1,2,3,4], ['a','b','c','d']):
    print i

The Quick Answer

Please show us the code surrounding where the error happened. But I think I can still give you a quick (and not necessarily good) solution.

turn this

for i in reversed(range(1, len(x))):

into this:

for i in reversed(range(1, len(list(x))):

In mnist_loader wrap your zip results in list() constructs like below

def load_data_wrapper():    
    tr_d, va_d, te_d = load_data()
    training_inputs = [np.reshape(x, (784,1)) for x in tr_d[0]]
    training_results = [vectorized_result(y) for y in tr_d[1]]
    training_data = list(zip(training_inputs, training_results))
    validation_inputs = [np.reshape(x,(784, 1))for x in va_d[0]]
    validation_data = list(zip(validation_inputs, va_d[1]))
    test_inputs = [np.reshape(x, (784, 1)) for x in te_d[0]]
    test_data = list(zip(test_inputs, te_d[1]))
    return(training_data, validation_data, test_data)