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import pafy
from pydub import AudioSegment
import argparse

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-u", "--url", required=True, help="download link")
args = vars(ap.parse_args())

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shravankumar147

iris["Species"] = iris["Species"].map({"Iris-setosa":0,"Iris-virginica":1,"Iris-versicolor":2})

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# Implementation of a simple MLP network with one hidden layer. Tested on the iris data set.
# Requires: numpy, sklearn>=0.18.1, tensorflow>=1.0

# NOTE: In order to make the code simple, we rewrite x * W_1 + b_1 = x' * W_1'
# where x' = [x | 1] and W_1' is the matrix W_1 appended with a new row with elements b_1's.
# Similarly, for h * W_2 + b_2
import tensorflow as tf
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split

shravankumar147

  from datetime import datetime                                                                                                                     
                                                                                                                                                    
                                                                                                                                                    
  def post_name(name):                                                                                                                              
      """                                                                                                                                           
      This will generate your github post name.                                                                                                     
      example:                                                                                                                    

shravankumar147

set nocompatible              " be iMproved, required
filetype off                  " required
set exrc

set rtp+=~/.vim/bundle/Vundle.vim
call vundle#begin()

" ==== PLUGINS ====
Plugin 'VundleVim/Vundle.vim'
Plugin 'vim-scripts/L9'

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# USAGE
# python face_detection.py --image face1.jpg

# import the necessary packages
# from imutils import face_utils
# import numpy as np
import argparse
import imutils
import dlib
import cv2

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shravankumar147

'''Trains a simple convnet on the MNIST dataset.

Gets to 98.97% test accuracy after 12 epochs
'''

from __future__ import print_function
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten

shravankumar147

How to use Pelican on GitHub Pages

Author: Josef Jezek

Install on Ubuntu

Installing Python tools

sudo apt-get install python-setuptools