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(async () => {
  function sleep(ms) {
    return new Promise(resolve => setTimeout(resolve, ms));
  }
  
  watchedVideoOverlays = Array.from(document.getElementsByClassName('ytd-thumbnail-overlay-resume-playback-renderer'))
  
  for(let i = 0; i < watchedVideoOverlays.length; i += 1){
    console.log(i)
    try{

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/**
USAGE
1. Open the playlist you want
2. Right click > Inspect element > Console
3. Copy this and paste. Hit enter.
4. For watch later make sure to click the Edit button

EDIT: Not all playlists have hours.
*/

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# http://www-01.sil.org/linguistics/wordlists/english/wordlist/wordsEn.txt
with open("./wordsEn.txt") as word_file:
    english_words = set(word.strip().lower() for word in word_file)

matches = []

WORD_LEN = 4

for word in english_words:
    if len(word) == WORD_LEN:

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var students = [];

var rows = $("tr");

for(var i = 1; i < rows.length; i++){
	students[i-1] = {};
	var row = rows[i];
	var name = (row.children[0].innerHTML+"").trim();
	students[i-1]["name"] = name.replace("&nbsp;","").replace(/\s\s+/g,' ');
	var cgpa = (row.children[3].innerHTML+"").trim();

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'''
SqueezeNet v1.1 (https://github.com/DeepScale/SqueezeNet/tree/master/SqueezeNet_v1.1)
Paper: https://arxiv.org/abs/1602.07360

TODO: Use Xavier initializer
'''

import tensorflow as tf

x = tf.placeholder(tf.float32,(None,28*28))

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/**
USAGE
1. Open the playlist you want
2. Right click > Inspect element > Console
3. Copy this and paste. Hit enter.
4. For watch later make sure to click the Edit button

Make sure &disable_polymer=true flag is set
e.g.
https://www.youtube.com/playlist?list=WL&disable_polymer=true

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class Main{
  public static void main(String[]args){
    float a = 5;
    float b = 6;
    System.out.println(Math.exp(Math.log(a)+Math.log(b)));
  }
}

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import matplotlib.pyplot as plt
from matplotlib import style
import numpy as np
style.use('ggplot')

class Support_Vector_Machine:
    def __init__(self, visualization=True):
        self.visualization = visualization
        self.colors = {1:'r',-1:'b'}
        if self.visualization:

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#include<stdio.h>
#include<stdlib.h>
#include<time.h>

#define FRAMES 4
#define	ITERATIONS 10

// Check if the page is already in the frame
int hasPageInFrame(int *a,int request){
	int i;

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from nltk.corpus import wordnet
from nltk.tokenize import word_tokenize
from random import randint
import nltk.data

# Load a text file if required
text = "Pete ate a large cake. Sam has a big mouth."
output = ""

# Load the pretrained neural net