A more consistent and multi-functional global level of verbosity control,
suggest an enhancement that will see print(...) in project be converted to using the python logging. module

import logging
#Then instead of print() use either
logging.info(......)
#or
logging.debug(.....)
#or
logging.warning(....)
#or
#logging.error()

In that way verbosity can be globally

This is from the documentation at http://docs.seldon.io/api-oauth.html#actions

The item attribute definition is:
string name [attr_id 1]
string artist [attr_id 2]
enum category [attr_id 3]
double price [attr_id 4]
Where:
category is the enumeration
** (pop [value_id 1], rock [value_id 2], rap [value_id 3])
a range definition is created for the price ** (<10 [value_id 1], 10-20 [value_id

Hi Steven, I don't know where else to ask so I'm asking here--

I'm following your useful XOR network tutorial and I'm confused by this step:

Once we get the delta hidden sum, we calculate the change in weights between the input and hidden layer by dividing it with the input data, (1, 1).

What if the input is (1, 0)

def get_all_words(self): """ Return all words tokenized, in lowercase and without punctuation """ return [w.lower() for w in word_tokenize(self.text) if w not in string.punctuation]
I found that in this function, only punctuation of the text was removed. But there are other types of words that have not been removed.
eg:
`from nltk.corpus import stopwords

Thanks for your explanation, can you please explain how you are calculating the speed in this block ?
Because I can't understand some of the transformations like scale_real_length, scale_real_time_passed, speed = speed/6*40 and scale = 1
please elaborate a bit.