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ssh-keygen -t rsa -b 4096 -N '' -C "[email protected]" -f ~/.ssh/id_rsa
ssh-keygen -t rsa -b 4096 -N '' -C "[email protected]" -f ~/.ssh/github_rsa
ssh-keygen -t rsa -b 4096 -N '' -C "[email protected]" -f ~/.ssh/mozilla_rsa

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Install and configure Sendmail on Ubuntu

This should help you get Sendmail installed with basic configuration on Ubuntu.

1. If sendmail isn't installed, install it: sudo apt-get install sendmail
2. Configure /etc/hosts file: nano /etc/hosts
3. Make sure the line looks like this: 127.0.0.1 localhost yourhostname
4. Run Sendmail's config and answer 'Y' to everything: sudo sendmailconfig
5. Restart apache sudo service apache2 restart

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#!/usr/bin/env bash
# https://developers.supportbee.com/blog/setting-up-cucumber-to-run-with-Chrome-on-Linux/
# https://gist.github.com/curtismcmullan/7be1a8c1c841a9d8db2c
# http://stackoverflow.com/questions/10792403/how-do-i-get-chrome-working-with-selenium-using-php-webdriver
# http://stackoverflow.com/questions/26133486/how-to-specify-binary-path-for-remote-chromedriver-in-codeception
# http://stackoverflow.com/questions/40262682/how-to-run-selenium-3-x-with-chrome-driver-through-terminal
# http://askubuntu.com/questions/760085/how-do-you-install-google-chrome-on-ubuntu-16-04

# Versions
CHROME_DRIVER_VERSION=`curl -sS chromedriver.storage.googleapis.com/LATEST_RELEASE`

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#!/bin/bash
# Author: tckb<[email protected]>
# Ping notification using terminal- notifier; for OsX
# Usuage: ./notify_ping.sh <check_freq_seconds> & 
rm $HOME/.np_click 2>/dev/null
if [ -z ${1} ]
	then
		freq=5 #check every 5 seconds
	else
		freq=$1

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from __future__ import print_function

import numpy as np
import pandas as pd
import talib as ta
import pandas_datareader as web

from sklearn.linear_model import LinearRegression
from sklearn.linear_model import Ridge
from sklearn.model_selection import cross_val_score

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import numpy as np
import pylab as pl
from numpy import fft
    
def fourierExtrapolation(x, n_predict):
    n = x.size
    n_harm = 10                     # number of harmonics in model
    t = np.arange(0, n)
    p = np.polyfit(t, x, 1)         # find linear trend in x
    x_notrend = x - p[0] * t        # detrended x