First of all install update and upgrade your system:
$ sudo apt update
$ sudo apt upgrade
Then, install required libraries:
class Spiderman { | |
lookOut() { | |
alert('My Spider-Sense is tingling.'); | |
} | |
} | |
let miles = new Spiderman(); | |
miles.lookOut(); |
#include <stdint.h> | |
#include <stdio.h> | |
#include <stdlib.h> | |
// munged from https://github.com/simontime/Resead | |
namespace sead | |
{ | |
class Random | |
{ |
<!DOCTYPE html> | |
<html> | |
<head> | |
<meta charset=utf-8> | |
<title>Fibonacci Sphere in ThreeJS</title> | |
<style> | |
body { | |
margin: 0; | |
} |
If you hate git submodule
, then you may want to give git subtree
a try.
When you want to use a subtree, you add the subtree to an existing repository where the subtree is a reference to another repository url and branch/tag. This add
command adds all the code and files into the main repository locally; it's not just a reference to a remote repo.
When you stage and commit files for the main repo, it will add all of the remote files in the same operation. The subtree checkout will pull all the files in one pass, so there is no need to try and connect to another repo to get the portion of subtree files, because they were already included in the main repo.
Let's say you already have a git repository with at least one commit. You can add another repository into this respository like this:
With the availability of huge amount of data for research and powerfull machines to run your code on, Machine Learning and Neural Networks is gaining their foot again and impacting us more than ever in our everyday lives. With huge players like Google opensourcing part of their Machine Learning systems like the TensorFlow software library for numerical computation, there are many options for someone interested in starting off with Machine Learning/Neural Nets to choose from. Caffe, a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and its contributors, comes to the play with a fresh cup of coffee.
The following section is divided in to two parts. Caffe's documentation suggest
Prerequisites : the letsencrypt CLI tool
This method allows your to generate and renew your Lets Encrypt certificates with 1 command. This is easily automatable to renew each 60 days, as advised.
You need nginx to answer on port 80 on all the domains you want a certificate for. Then you need to serve the challenge used by letsencrypt on /.well-known/acme-challenge
.
Then we invoke the letsencrypt command, telling the tool to write the challenge files in the directory we used as a root in the nginx configuration.
I redirect all HTTP requests on HTTPS, so my nginx config looks like :
server {
#!/usr/bin/env python | |
# gpu_stat.py [DELAY [COUNT]] | |
# dump some gpu stats as a line of json | |
# {"util":{"PCIe":"0", "memory":"11", "video":"0", "graphics":"13"}, "used_mem":"161"} | |
import json, socket, subprocess, sys, time | |
try: | |
delay = int(sys.argv[1]) | |
except: | |
delay = 1 |