mmmayo13

from math import sqrt, floor
import numpy as np


def random(ds, k, random_state=42):
    """
    Create random cluster centroids.
    
    Parameters
    ----------

mmmayo13

from collections import Counter
from string import punctuation
from sklearn.feature_extraction.stop_words import ENGLISH_STOP_WORDS as stop_words
import spacy

def count_words(tokens):
    word_counts = {}
    for token in tokens:
        if token not in stop_words and token not in punctuation and token is not '\n':
            if token not in word_counts.keys():

mmmayo13

class Vocabulary:
    PAD_token = 0   # Used for padding short sentences
    SOS_token = 1   # Start-of-sentence token
    EOS_token = 2   # End-of-sentence token

    def __init__(self, name):
        self.name = name
        self.word2index = {}
        self.word2count = {}
        self.index2word = {PAD_token: "PAD", SOS_token: "SOS", EOS_token: "EOS"}

mmmayo13

import os

import speech_recognition as sr

from pydub import AudioSegment
from pydub.playback import play
from gtts import gTTS as tts


def speak(text):

mmmayo13

import numpy

import GA



"""

The y=target is to maximize this equation ASAP:

mmmayo13

from keras import models
from keras.layers import Dense, Dropout
from keras.utils import to_categorical
from keras.datasets import mnist
from keras.utils.vis_utils import model_to_dot
from IPython.display import SVG

import livelossplot
plot_losses = livelossplot.PlotLossesKeras()

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#Install the Ecdat package
install.packages("Ecdat")
#Loading the library and the Garch dataset
library(Ecdat)
mydata=Garch
#Look at the dataset
str(mydata)

#Correct the data types of date and day
#Correcting date fixes it to some arbitrary date such that the trend is same but the mapping is different

mmmayo13

def stem_and_lemmatize(words):
    stems = stem_words(words)
    lemmas = lemmatize_verbs(words)
    return stems, lemmas

stems, lemmas = stem_and_lemmatize(words)
print('Stemmed:\n', stems)
print('\nLemmatized:\n', lemmas)

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sample = """Title Goes Here
Bolded Text
Italicized Text

But this will still be here!

I run. He ran. She is running. Will they stop running?

I talked. She was talking. They talked to them about running. Who ran to the talking runner?

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sample = """<h1>Title Goes Here</h1>

<b>Bolded Text</b>
<i>Italicized Text</i>

<img src="this should all be gone"/>

<a href="this will be gone, too">But this will still be here!</a>

I run. He ran. She is running. Will they stop running?