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Dviejo Dviejopomata

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View main.dart
import 'package:flutter/material.dart';
final Color darkBlue = Color.fromARGB(255, 18, 32, 47);
void main() {
runApp(MyApp());
}
class MyApp extends StatelessWidget {
@override
View load_dynamic_angular.js
window.PATH = "{{ client_path }}";
$(document).ready(function () {
function loadStyle(src) {
var s = document.createElement("link");
s.rel = "stylesheet";
s.src = src;
// Use any selector
$("head").append(s);
}
View q.py
import itertools
import random
import numpy as np
class Game:
def __init__(self):
"""
0 - casilla vacia
View qtable.py
import itertools
import random
import numpy as np
from loguru import logger
def my_filter(record):
if "warn_only" in record["extra"]:
return record["level"].no >= logger.level("WARNING").no
View rl.py
import random
import gym
import numpy as np
from collections import deque
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import Adam
from keras.models import load_model
# from scores.score_logger import ScoreLogger
View bill_authentication.csv
Variance Skewness Curtosis Entropy Class
3.6216 8.6661 -2.8073 -0.44699 0
4.5459 8.1674 -2.4586 -1.4621 0
3.866 -2.6383 1.9242 0.10645 0
3.4566 9.5228 -4.0112 -3.5944 0
0.32924 -4.4552 4.5718 -0.9888 0
4.3684 9.6718 -3.9606 -3.1625 0
3.5912 3.0129 0.72888 0.56421 0
2.0922 -6.81 8.4636 -0.60216 0
3.2032 5.7588 -0.75345 -0.61251 0
View car.csv
PRICE MAINT DOORS PERSONS SAFETY CLASS
40000 2000 2 2 low unacc
40000 2000 2 2 med unacc
40000 2000 2 2 high unacc
40000 2000 2 2 low unacc
40000 2000 2 2 med unacc
40000 2000 2 2 high unacc
40000 2000 2 2 low unacc
40000 2000 2 2 med unacc
40000 2000 2 2 high unacc
View square_root.py
import time
import keras
import matplotlib.pyplot as plt
import numpy as np
from keras.layers import Dense, Activation
from keras.models import Sequential
x = np.arange(-100, 100, 0.5)
y = x ** 2
View n.py
#%%
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from scipy.cluster.hierarchy import dendrogram, linkage
from sklearn import datasets
import seaborn as sns
%matplotlib inline
sns.set(style="darkgrid")
#%%
View ribbon.xml
<?xml version="1.0" encoding="UTF-8"?>
<customUI xmlns="http://schemas.microsoft.com/office/2009/07/customui" onLoad="Ribbon_Load">
<ribbon>
<tabs>
<tab idMso="TabAddIns" label="Docxmerge">
<group id="ContentGroup" label="Template actions">
<button id="textButton" label="Upload"
screentip="Text" onAction="OnTextButton"
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