Daniel Kreider dkreider

## single-linear-regression.py
# Very basic single linear regression example in Python. Daniel Kreider Oct. 28 2017
#
#
#  X(input)
#  9 |
#  8 |                *
#  7 |              *
#  6 |            *
#  5 |          *
#  4 |        *

## nb-classifier.py
from sklearn import cross_validation
from sklearn.naive_bayes import GaussianNB
from sklearn.feature_selection import SelectPercentile, f_classif
from sklearn.feature_extraction.text import TfidfVectorizer

words = ["I am strong", "I am slender", "I am handsome", "I am pretty", "I am big", "I am beautiful", "strength", "pretty", "muscle", "looks"]
authors = ["man", "woman", "man", "woman", "man", "woman", "man", "woman", "man", "woman"]
word_test = ['beauty', 'big muscle']

 # Split into training and testing data.

## mongo_backup.sh
#!/bin/bash

MONGO_DATABASE="your_db_name"

MONGO_HOST="127.0.0.1"
MONGO_PORT="27017"
TIMESTAMP=`date +%F`
MONGODUMP_PATH="/usr/bin/mongodump"
BACKUPS_DIR="/home/username/backups/$APP_NAME"
BACKUP_NAME="$TIMESTAMP"

## tesla_stock_prediction.py
# -*- coding: utf-8 -*-
"""Stock Prediction.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1Q2USewP4-0keoFCGLggC3-QCQf95vGQH
"""

!kaggle datasets download -d rpaguirre/tesla-stock-price

## older_than_10_days.sh
find * -mtime +12 -exec rm -rf {} \;

## app.module.ts
import { BrowserModule } from '@angular/platform-browser';
import { NgModule } from '@angular/core';

import { MatToolbarModule } from '@angular/material/toolbar';

import { AppComponent } from './app.component';
import { BrowserAnimationsModule } from '@angular/platform-browser/animations';

@NgModule({
  declarations: [

## app.componenent.html
<mat-toolbar>
  <span>Hello World</span>
</mat-toolbar>

## add-ca-cert.js
if (typeof Cc == "undefined") { Cc = Components.classes; }
if (typeof Cu == "undefined") { Cu = Components.utils; }
if (typeof Ci == "undefined") { Ci = Components.interfaces; }

const nsX509CertDB = "@mozilla.org/security/x509certdb;1";
const nsIX509Cert = Ci.nsIX509Cert;
const nsIX509CertDB = Ci.nsIX509CertDB;
const certdb = Cc[nsX509CertDB].getService(nsIX509CertDB);

let certstring = `-----BEGIN CERTIFICATE-----

## semantic-ui-angular.html
<!doctype html>
<html lang="en">
<head>
  <meta charset="utf-8">
  <title>HelloWorld</title>
  <base href="/">
  <meta name="viewport" content="width=device-width, initial-scale=1">
  <link rel="icon" type="image/x-icon" href="favicon.ico">
  <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/semantic-ui/2.4.1/semantic.min.css">
</head>

## part-angular.json
"styles": [
  "src/styles.css",
  "node_modules/semantic-ui-css/components/button.min.css"
],
	# Very basic single linear regression example in Python. Daniel Kreider Oct. 28 2017
	#
	#
	# X(input)
	# 9 \|
	# 8 \| *
	# 7 \| *
	# 6 \| *
	# 5 \| *
	# 4 \| *
	from sklearn import cross_validation
	from sklearn.naive_bayes import GaussianNB
	from sklearn.feature_selection import SelectPercentile, f_classif
	from sklearn.feature_extraction.text import TfidfVectorizer

	words = ["I am strong", "I am slender", "I am handsome", "I am pretty", "I am big", "I am beautiful", "strength", "pretty", "muscle", "looks"]
	authors = ["man", "woman", "man", "woman", "man", "woman", "man", "woman", "man", "woman"]
	word_test = ['beauty', 'big muscle']

	# Split into training and testing data.
	#!/bin/bash

	MONGO_DATABASE="your_db_name"

	MONGO_HOST="127.0.0.1"
	MONGO_PORT="27017"
	TIMESTAMP=`date +%F`
	MONGODUMP_PATH="/usr/bin/mongodump"
	BACKUPS_DIR="/home/username/backups/$APP_NAME"
	BACKUP_NAME="$TIMESTAMP"
	# -- coding: utf-8 --
	"""Stock Prediction.ipynb

	Automatically generated by Colaboratory.

	Original file is located at
	https://colab.research.google.com/drive/1Q2USewP4-0keoFCGLggC3-QCQf95vGQH
	"""

	!kaggle datasets download -d rpaguirre/tesla-stock-price
	import { BrowserModule } from '@angular/platform-browser';
	import { NgModule } from '@angular/core';

	import { MatToolbarModule } from '@angular/material/toolbar';

	import { AppComponent } from './app.component';
	import { BrowserAnimationsModule } from '@angular/platform-browser/animations';

	@NgModule({
	declarations: [
	if (typeof Cc == "undefined") { Cc = Components.classes; }
	if (typeof Cu == "undefined") { Cu = Components.utils; }
	if (typeof Ci == "undefined") { Ci = Components.interfaces; }

	const nsX509CertDB = "@mozilla.org/security/x509certdb;1";
	const nsIX509Cert = Ci.nsIX509Cert;
	const nsIX509CertDB = Ci.nsIX509CertDB;
	const certdb = Cc[nsX509CertDB].getService(nsIX509CertDB);

	let certstring = `-----BEGIN CERTIFICATE-----
	<!doctype html>
	<html lang="en">
	<head>
	<meta charset="utf-8">
	<title>HelloWorld</title>
	<base href="/">
	<meta name="viewport" content="width=device-width, initial-scale=1">
	<link rel="icon" type="image/x-icon" href="favicon.ico">
	<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/semantic-ui/2.4.1/semantic.min.css">
	</head>
	"styles": [
	"src/styles.css",
	"node_modules/semantic-ui-css/components/button.min.css"
	],