Dustin Alandzes DustinAlandzes

## webcam-cv2.py
'''
Simply display the contents of the webcam with optional mirroring using OpenCV
via the new Pythonic cv2 interface.  Press <esc> to quit.
'''

import cv2

def show_webcam(mirror=False):
  cam = cv2.VideoCapture(0)
	while True:

## FFMPEG_Notes.md

      
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                DustinAlandzes
                / FFMPEG_Notes.md
            
            
              Created
              August 7, 2017 20:33
                — forked from pjobson/FFMPEG_Notes.md
            
              
                FFMPEG Notes
              
          
    Some Recipies for ffmpeg Usage

I screw around with ffmpeg a lot, here are some recipies which I frequently use.
AUDIO

... to MP3

ffmpeg -i <input>.wav -codec:a libmp3lame -b:a 320k output.mp3

ffmpeg -i .wav -codec:a libmp3lame -q:a 0 output.mp3

  
## probereq-flooder.py
#!/usr/bin/env python

# This script generates high volume of 802.11 Probe Requests frames.
# Each frame have uniq random source MAC.
# It use Scapy http://www.secdev.org/projects/scapy/ for frames crafting.
# You need injection supported device.

import logging
logging.getLogger("scapy.runtime").setLevel(logging.ERROR) # Disable IPv6 warnings

## index.html
<!DOCTYPE html>
<html lang="en">
  <head>
    <!-- Required meta tags -->
    <meta charset="utf-8">
    <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">

    <!-- Bootstrap CSS -->
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta/css/bootstrap.min.css" integrity="sha384-/Y6pD6FV/Vv2HJnA6t+vslU6fwYXjCFtcEpHbNJ0lyAFsXTsjBbfaDjzALeQsN6M" crossorigin="anonymous">
  <style id="jsbin-css">

## Vehicle Purchasing - Linear Regression, Random Forest Regression .ipynb

      
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                DustinAlandzes
                / Vehicle Purchasing - Linear Regression, Random Forest Regression .ipynb
            
            
              Created
              September 23, 2017 05:37
                — forked from JJRyan0/Vehicle Purchasing - Linear Regression, Random Forest Regression .ipynb
            
              
                Data Science Tutorial - Random Forest Regression.ipynb
              
          
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## Advanced Data Analysis; Multiple Linear Regression and One-way ANOVA using R.ipynb

      
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                DustinAlandzes
                / Advanced Data Analysis; Multiple Linear Regression and One-way ANOVA using R.ipynb
            
            
              Created
              September 23, 2017 05:37
                — forked from JJRyan0/Advanced Data Analysis; Multiple Linear Regression and One-way ANOVA using R.ipynb
            
              
                Advanced Data Analysis; Multiple Linear Regression and One-way ANOVA using R.ipynb
              
          
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## Gradient Boosting Machines v.s Decision Tree Demo 99.30% Acc - Sklearn.ipynb

      
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                DustinAlandzes
                / Gradient Boosting Machines v.s  Decision Tree Demo 99.30% Acc - Sklearn.ipynb
            
            
              Created
              September 23, 2017 05:37
                — forked from JJRyan0/Gradient Boosting Machines v.s  Decision Tree Demo 99.30% Acc - Sklearn.ipynb
            
              
                Gradient Boosting Machines Out of Bag - Sklearn.ipynb
              
          
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## gist:18cf9f394addfb030a05a16eca68dc4f
"""
This is a batched LSTM forward and backward pass
"""
import numpy as np
import code

class LSTM:

  @staticmethod
  def init(input_size, hidden_size, fancy_forget_bias_init = 3):

## ANOVA.ipynb

      
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                DustinAlandzes
                / ANOVA.ipynb
            
            
              Created
              September 23, 2017 20:15
                — forked from tlinnet/ANOVA.ipynb
            
              
                ANOVA in python
              
          
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## wfc.js
//single file version of https://github.com/kchapelier/wavefunctioncollapse

function randomIndice (array, r) {
    var sum = 0,
        i,
        x;

    for (i = 0; i < array.length; i++) {
        sum += array[i];
    }
	'''
	Simply display the contents of the webcam with optional mirroring using OpenCV
	via the new Pythonic cv2 interface. Press <esc> to quit.
	'''

	import cv2

	def show_webcam(mirror=False):
	cam = cv2.VideoCapture(0)
	while True:
	#!/usr/bin/env python

	# This script generates high volume of 802.11 Probe Requests frames.
	# Each frame have uniq random source MAC.
	# It use Scapy http://www.secdev.org/projects/scapy/ for frames crafting.
	# You need injection supported device.

	import logging
	logging.getLogger("scapy.runtime").setLevel(logging.ERROR) # Disable IPv6 warnings
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<!-- Required meta tags -->
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">

	<!-- Bootstrap CSS -->
	<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta/css/bootstrap.min.css" integrity="sha384-/Y6pD6FV/Vv2HJnA6t+vslU6fwYXjCFtcEpHbNJ0lyAFsXTsjBbfaDjzALeQsN6M" crossorigin="anonymous">
	<style id="jsbin-css">
	"""
	This is a batched LSTM forward and backward pass
	"""
	import numpy as np
	import code

	class LSTM:

	@staticmethod
	def init(input_size, hidden_size, fancy_forget_bias_init = 3):
	//single file version of https://github.com/kchapelier/wavefunctioncollapse

	function randomIndice (array, r) {
	var sum = 0,
	i,
	x;

	for (i = 0; i < array.length; i++) {
	sum += array[i];
	}