Mr. Steve Charlesworth stephen-charlesworth-milliman

Create a service file like dash_sniffer.service
Put it in /lib/systemd/system/
Reload systemd using command: systemctl daemon-reload
Enable auto start using command: systemctl enable dash_sniffer.service

A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

Stevey's Google Platforms Rant

I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.

I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real

	import com.neuronrobotics.sdk.dyio.DyIO;
	import com.neuronrobotics.sdk.ui.ConnectionDialog;
	ScriptingEngine.gitScriptRun(
	"https://github.com/CommonWealthRobotics/BowlerCom.git", // git location of the library
	"examples/DyIOLargeChip/DyIOLargeChip.ino" , // Arduino DyIo default firmware
	null
	);


	System.out.println("Starting");

	# extracted from http//www.naturalearthdata.com/download/110m/cultural/ne_110m_admin_0_countries.zip
	# under public domain terms

	country_bounding_boxes = {
	'AF': ('Afghanistan', (60.5284298033, 29.318572496, 75.1580277851, 38.4862816432)),
	'AO': ('Angola', (11.6400960629, -17.9306364885, 24.0799052263, -4.43802336998)),
	'AL': ('Albania', (19.3044861183, 39.624997667, 21.0200403175, 42.6882473822)),
	'AE': ('United Arab Emirates', (51.5795186705, 22.4969475367, 56.3968473651, 26.055464179)),
	'AR': ('Argentina', (-73.4154357571, -55.25, -53.628348965, -21.8323104794)),
	'AM': ('Armenia', (43.5827458026, 38.7412014837, 46.5057198423, 41.2481285671)),

	#Write geojson
	#====

	#Load libraries
	library(rgdal)

	#dataMap is a dataframe with coordinates on cols 11 (LATITUDE) and 12 (LONGITUDE)
	#Transfor coordinates to numeric
	dataMap$LATITUDE <- as.numeric(dataMap$LATITUDE)
	dataMap$LONGITUDE <- as.numeric(dataMap$LONGITUDE)

	## Example procedure for working with data (attributes) inside SpatialPolygonsDataFrame objects

	# Load my favorite libraries for that sort of work
	library(data.table)
	library(rgdal)

	# Load 2 shapefiles that, say, we want to merge.
	# Note that you can read pretty much any spatial format using readOGR().
	tza.l2 <- readOGR("./analysis/TZA-AC-07/maps", "tza-ac-07_L2")
	tza.l1 <- readOGR("./analysis/TZA-AC-07/maps", "tza-ac-07_L1")