dupuy

Markdown and reStructuredText

GitHub supports several lightweight markup languages for documentation; the most popular ones (generally, not just at GitHub) are Markdown and reStructuredText. Markdown is sometimes considered easier to use, and is often preferred when the purpose is simply to generate HTML. On the other hand, reStructuredText is more extensible and powerful, with native support (not just embedded HTML) for tables, as well as things like automatic generation of tables of contents.

captn3m0

This document is guided at SDSLabs members, but should be equally valid to anyone working in technology.

I've tried to keep all advice language agnostic and independent from any technology. This is like a series of short blog posts I've condensed to a single gist. Feel free to fork and give some more of such advice.

dypsilon

Frontend Development

Attention: the list was moved to

https://github.com/dypsilon/frontend-dev-bookmarks

This page is not maintained anymore, please update your bookmarks.

---

dypsilon

Backend Development

• node.js
  • Installation paths: use one of these techniques to install node and npm without having to sudo.
  • Node.js HOWTO: Install Node+NPM as user (not root) under Unix OSes
  • Felix's Node.js Guide
  • Creating a REST API using Node.js, Express, and MongoDB
  • Node Cellar Sample Application with Backbone.js, Twitter Bootstrap, Node.js, Express, and MongoDB
  • JavaScript Event Loop
• Node.js for PHP programmers

pythonicrubyist

sudo apt-get install dkms build-essential linux-headers-generic
# On virtual machine’s menu bar on top, click on Device/Install Guest Additions. This will launch a unix script runing on the Ubuntu terminal.
sudo reboot

alexlee-gk

This was tested on a ThinkPad P70 laptop with an Intel integrated graphics and an NVIDIA GPU:

lspci | egrep 'VGA|3D'
00:02.0 VGA compatible controller: Intel Corporation Device 191b (rev 06)
01:00.0 VGA compatible controller: NVIDIA Corporation GM204GLM [Quadro M3000M] (rev a1)

A reason to use the integrated graphics for display is if installing the NVIDIA drivers causes the display to stop working properly. In my case, Ubuntu would get stuck in a login loop after installing the NVIDIA drivers. This happened regardless if I installed the drivers from the "Additional Drivers" tab in "System Settings" or the ppa:graphics-drivers/ppa in the command-line.

Brainiarc7

Building Tensorflow from source on Ubuntu 16.04LTS for maximum performance:

TensorFlow is now distributed under an Apache v2 open source license on GitHub.

On Ubuntu 16.04LTS+:

Step 1. Install NVIDIA CUDA:

To use TensorFlow with NVIDIA GPUs, the first step is to install the CUDA Toolkit as shown:

se7oluti0n

import sys
sys.path.append('../../facenet/src')

import facenet
import argparse
import os
import importlib
import tensorflow as tf
from tqdm import tqdm
import tensorflow.contrib.slim as slim

ColeMurray

FROM tensorflow/tensorflow:latest

RUN apt-get update -y --fix-missing
RUN apt-get install -y ffmpeg
RUN apt-get install -y build-essential cmake pkg-config \
                    libjpeg8-dev libtiff5-dev libjasper-dev libpng12-dev \
                    libavcodec-dev libavformat-dev libswscale-dev libv4l-dev \
                    libxvidcore-dev libx264-dev \
                    libgtk-3-dev \
                    libatlas-base-dev gfortran \

peterroelants

from __future__ import division, print_function, absolute_import, \
    unicode_literals

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data as mnist_data
from tensorflow.contrib import slim
from tensorflow.contrib.learn import ModeKeys
from tensorflow.contrib.learn.python.learn import learn_runner