carlos-aguayo

license: gpl-3.0

carlos-aguayo

The Project Gutenberg EBook of The Republic, by Plato

This eBook is for the use of anyone anywhere at no cost and with
almost no restrictions whatsoever.  You may copy it, give it away or
re-use it under the terms of the Project Gutenberg License included
with this eBook or online at www.gutenberg.org


Title: The Republic

carlos-aguayo

carlos-aguayo

carlos-aguayo

carlos-aguayo

__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_1 (InputLayer)            (None, None, None, 3 0                                            
__________________________________________________________________________________________________
conv2d_1 (Conv2D)               (None, None, None, 3 864         input_1[0][0]                    
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, None, None, 3 96          conv2d_1[0][0]                   
__________________________________________________________________________________________________
activation_1 (Activation)       (None, None, None, 3 0           batch_normalization_1[0][0]      

carlos-aguayo

from selenium import webdriver
from BeautifulSoup import BeautifulSoup
import requests

options = webdriver.ChromeOptions()
options.add_argument('headless')
driver = webdriver.Chrome(chrome_options=options)
driver.set_window_size(1280, 1600)

filename = 'NOTICE.html'

carlos-aguayo

from jira import JIRA
from dateutil.parser import parse
import pandas as pd

# For any ticket that was externally reported or labeled a hotfix in the last 90 days, compute:
# 1. Number of comments
# 2. How long it took for it to be labeled hotfix
# 3. Number of transitions across squads

username = 'carlos.aguayo'

carlos-aguayo

import pandas as pd
from xgboost import XGBClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.preprocessing import LabelEncoder

dataset = pd.read_csv('https://github.com/primaryobjects/voice-gender/raw/master/voice.csv', header=0).values
x = dataset[:, :-1]
y = dataset[:, -1]

carlos-aguayo

import gym
import pandas as pd
import numpy as np
import random

# https://gym.openai.com/envs/CartPole-v0
# Carlos Aguayo - carlos.aguayo@gmail.com


class QLearner(object):