smellslikeml smellslikeml

## zipcode_lookup.sh
#!/bin/bash
# zipcode--Given a ZIP code, identifies the city and state. Use city-data.com,
#   which has every ZIP code configured as its own web page.
baseURL="http://www.city-data.com/zips"
/bin/echo -n "ZIP code $1 is in "
curl -s -dump "$baseURL/$1.html" | \
  grep -i '<title>' | \
  cut -d\( -f2 | cut -d\) -f1
exit 0

## tweet_logger.py
#!/usr/bin/env python
import sys
from datetime import datetime
import os
import json
from tweepy import OAuthHandler
from tweepy import Stream
from tweepy.streaming import StreamListener

consumer_key = os.environ['CONSUMER_KEY']

## tweepy_streamer.py
#!/usr/bin/env python
import os
import sys
from tweepy import OAuthHandler
from tweepy import Stream
from tweepy.streaming import StreamListener
import json
import socket

consumer_key = os.environ['CONSUMER_KEY']

## bte_rssi.py
#!/usr/bin/env python
import subprocess


def rssi_vals(addr):
    try:
        p = subprocess.Popen('sudo btmgmt find | grep {}'.format(addr), stdout=subprocess.PIPE, shell=True)
        a, b = p.communicate()
        read_lst = []
        for reading in str(a).split('\\n')[:-1]:

## w2v_tSNE_plot.py
#!/usr/bin/python
import sys
import re
import string
from gensim.models import Word2Vec, Phrases
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt
from nltk.corpus import stopwords
from itertools import islice

## yt_download.py
#!/usr/bin/env python
import os
import sys
import requests
from bs4 import BeautifulSoup as bs
from urllib.parse import urlencode
from pytube import YouTube

qstring = sys.argv[1]
out_dir = sys.argv[2]

## anom_droop.ipynb

      
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                smellslikeml
                / anom_droop.ipynb
            
            
              Created
              February 23, 2019 22:52
            
              
                anomaly detection on droop counts
              
          
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## lambda_function.py
from __future__ import print_function
import os
import io
import boto3
import base64
import numpy as np
import zipfile
from PIL import Image
from tflite_runtime.interpreter import Interpreter

## youtube_downloader.py
import pytube

def yt_download(video_id, video_path):
    video_url = 'https://youtu.be/{}'.format(video_id)
    youtube = pytube.YouTube(video_url)
    video = youtube.streams.first()
    video.download(video_path)
    print('youtube video {} saved as: \n\n {}{}.mp4'.format(video_id, video_path, video.title))


## visual_anomaly_detection_demo.py
#!/usr/bin/python3
from __future__ import absolute_import, print_function
import cv2
import numpy as np
from time import sleep, time
from collections import deque

from tensorflow.keras.models import Model
from tensorflow.keras.optimizers import RMSprop
from tensorflow.keras.layers import Input, Conv2D, MaxPooling2D, UpSampling2D, ZeroPadding2D
	#!/bin/bash
	# zipcode--Given a ZIP code, identifies the city and state. Use city-data.com,
	# which has every ZIP code configured as its own web page.
	baseURL="http://www.city-data.com/zips"
	/bin/echo -n "ZIP code $1 is in "
	curl -s -dump "$baseURL/$1.html" \| \
	grep -i '<title>' \| \
	cut -d\( -f2 \| cut -d\) -f1
	exit 0
	#!/usr/bin/env python
	import sys
	from datetime import datetime
	import os
	import json
	from tweepy import OAuthHandler
	from tweepy import Stream
	from tweepy.streaming import StreamListener

	consumer_key = os.environ['CONSUMER_KEY']
	#!/usr/bin/env python
	import subprocess


	def rssi_vals(addr):
	try:
	p = subprocess.Popen('sudo btmgmt find \| grep {}'.format(addr), stdout=subprocess.PIPE, shell=True)
	a, b = p.communicate()
	read_lst = []
	for reading in str(a).split('\\n')[:-1]:
	#!/usr/bin/python
	import sys
	import re
	import string
	from gensim.models import Word2Vec, Phrases
	from sklearn.manifold import TSNE
	import matplotlib.pyplot as plt
	from nltk.corpus import stopwords
	from itertools import islice
	from __future__ import print_function
	import os
	import io
	import boto3
	import base64
	import numpy as np
	import zipfile
	from PIL import Image
	from tflite_runtime.interpreter import Interpreter
	import pytube

	def yt_download(video_id, video_path):
	video_url = 'https://youtu.be/{}'.format(video_id)
	youtube = pytube.YouTube(video_url)
	video = youtube.streams.first()
	video.download(video_path)
	print('youtube video {} saved as: \n\n {}{}.mp4'.format(video_id, video_path, video.title))
	#!/usr/bin/python3
	from __future__ import absolute_import, print_function
	import cv2
	import numpy as np
	from time import sleep, time
	from collections import deque

	from tensorflow.keras.models import Model
	from tensorflow.keras.optimizers import RMSprop
	from tensorflow.keras.layers import Input, Conv2D, MaxPooling2D, UpSampling2D, ZeroPadding2D