John Keefe jkeefe

## .eslintrc.js
{
  "env": {
    "browser": true,
    "node": true,
    "es6": true
  },

  "plugins": ["react"],

  "ecmaFeatures": {

## remove_exif.md

      
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                jkeefe
                / remove_exif.md
            
            
              Created Oct 14, 2020
            
              
                Remove EXIF from images with imagemagick
              
          
      View remove_exif.md
  
      
    Removing EXIF
Using Imagemagick:
cd into the directory with lots of images
mogrify -strip ./*.jpg

  
## class_06_block_7.html
<html lang="en">

  <head>
    <title>Newmark Bark</title>
    <meta name="description" content="latest news">
    <meta charset="utf-8">
    <meta http-equiv="X-UA-Compatible" content="IE=edge">
    <meta name="viewport" content="width=device-width, initial-scale=1">

    <!-- import the webpage's stylesheet -->

## lambda.js
// 1. This uses claudiajs & its API Gateway to deploy to lambda & handle api post

// 2. Assumes an existing dialogflow project, google cloud project, and google cloud billing

// 3. Got credentials .json file using steps 1-5 (ONLY) here:
//      https://cloud.google.com/docs/authentication/getting-started

// 4. Put that json file in a directory called "sekrets' which I added to .gitignore

// 5. Other helpful options for Google authentication are here:

## fish_tank.ino
#include <Adafruit_NeoPixel.h>

#define PIN1 6
#define PIN2 3

#define NUM_LEDS 60

#define BRIGHTNESS 250

int blue_every = 12;  // make every Xth pixel blue

## sratch.py
import pandas as pd
import pymysql

host="very.long.endpoint.definition.amazonaws.com"
port=3306
dbname="your_database_name"
user="your_user_name"
password="your_password"

conn = pymysql.connect(host, user=user,port=port,

## feature_importance.py
# Originally shared by Zachary Mueller here:
# https://forums.fast.ai/t/feature-importance-in-deep-learning/42026/16
# ... which he adapted from Miguel Mota Pinto's post here:
# https://medium.com/@mp.music93/neural-networks-feature-importance-with-fastai-5c393cf65815

# Assumes all necessary fast.ai v1.0 libraries are loaded

def feature_importance(learner):
  # based on: https://medium.com/@mp.music93/neural-networks-feature-importance-with-fastai-5c393cf65815
    data = learner.data.train_ds.x

## encryption.js
'use strict';

const crypto = require('crypto');

const ENCRYPTION_KEY = process.env.ENCRYPTION_KEY; // Must be 256 bytes (32 characters)
const IV_LENGTH = 16; // For AES, this is always 16

function encrypt(text) {
  let iv = crypto.randomBytes(IV_LENGTH);
  let cipher = crypto.createCipheriv('aes-256-cbc', new Buffer(ENCRYPTION_KEY), iv);

## index.js
var twilio = require('twilio');
var mongodb = require('mongodb');

module.exports = function(request) {

  return new Promise(function(fulfill, reject){

    // functional code goes in here

  });

## bot.js
'use strict';

/**
 * This sample demonstrates a simple skill built with the Amazon Alexa Skills Kit.
 * The Intent Schema, Custom Slots, and Sample Utterances for this skill, as well as
 * testing instructions are located at http://amzn.to/1LzFrj6
 *
 * For additional samples, visit the Alexa Skills Kit Getting Started guide at
 * http://amzn.to/1LGWsLG
 */
	{
	"env": {
	"browser": true,
	"node": true,
	"es6": true
	},

	"plugins": ["react"],

	"ecmaFeatures": {
	<html lang="en">

	<head>
	<title>Newmark Bark</title>
	<meta name="description" content="latest news">
	<meta charset="utf-8">
	<meta http-equiv="X-UA-Compatible" content="IE=edge">
	<meta name="viewport" content="width=device-width, initial-scale=1">

	<!-- import the webpage's stylesheet -->
	// 1. This uses claudiajs & its API Gateway to deploy to lambda & handle api post

	// 2. Assumes an existing dialogflow project, google cloud project, and google cloud billing

	// 3. Got credentials .json file using steps 1-5 (ONLY) here:
	// https://cloud.google.com/docs/authentication/getting-started

	// 4. Put that json file in a directory called "sekrets' which I added to .gitignore

	// 5. Other helpful options for Google authentication are here:
	#include <Adafruit_NeoPixel.h>

	#define PIN1 6
	#define PIN2 3

	#define NUM_LEDS 60

	#define BRIGHTNESS 250

	int blue_every = 12; // make every Xth pixel blue
	import pandas as pd
	import pymysql

	host="very.long.endpoint.definition.amazonaws.com"
	port=3306
	dbname="your_database_name"
	user="your_user_name"
	password="your_password"

	conn = pymysql.connect(host, user=user,port=port,
	# Originally shared by Zachary Mueller here:
	# https://forums.fast.ai/t/feature-importance-in-deep-learning/42026/16
	# ... which he adapted from Miguel Mota Pinto's post here:
	# https://medium.com/@mp.music93/neural-networks-feature-importance-with-fastai-5c393cf65815

	# Assumes all necessary fast.ai v1.0 libraries are loaded

	def feature_importance(learner):
	# based on: https://medium.com/@mp.music93/neural-networks-feature-importance-with-fastai-5c393cf65815
	data = learner.data.train_ds.x
	'use strict';

	const crypto = require('crypto');

	const ENCRYPTION_KEY = process.env.ENCRYPTION_KEY; // Must be 256 bytes (32 characters)
	const IV_LENGTH = 16; // For AES, this is always 16

	function encrypt(text) {
	let iv = crypto.randomBytes(IV_LENGTH);
	let cipher = crypto.createCipheriv('aes-256-cbc', new Buffer(ENCRYPTION_KEY), iv);
	var twilio = require('twilio');
	var mongodb = require('mongodb');

	module.exports = function(request) {

	return new Promise(function(fulfill, reject){

	// functional code goes in here

	});
	'use strict';

	/**
	* This sample demonstrates a simple skill built with the Amazon Alexa Skills Kit.
	* The Intent Schema, Custom Slots, and Sample Utterances for this skill, as well as
	* testing instructions are located at http://amzn.to/1LzFrj6
	*
	* For additional samples, visit the Alexa Skills Kit Getting Started guide at
	* http://amzn.to/1LGWsLG
	*/