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@TSiege
TSiege / The Technical Interview Cheat Sheet.md
Last active Apr 10, 2021
This is my technical interview cheat sheet. Feel free to fork it or do whatever you want with it. PLEASE let me know if there are any errors or if anything crucial is missing. I will add more links soon.
View The Technical Interview Cheat Sheet.md

ANNOUNCEMENT

I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!






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@piscisaureus
piscisaureus / pr.md
Created Aug 13, 2012
Checkout github pull requests locally
View pr.md

Locate the section for your github remote in the .git/config file. It looks like this:

[remote "origin"]
	fetch = +refs/heads/*:refs/remotes/origin/*
	url = git@github.com:joyent/node.git

Now add the line fetch = +refs/pull/*/head:refs/remotes/origin/pr/* to this section. Obviously, change the github url to match your project's URL. It ends up looking like this:

View Makefile
# Hello, and welcome to makefile basics.
#
# You will learn why `make` is so great, and why, despite its "weird" syntax,
# it is actually a highly expressive, efficient, and powerful way to build
# programs.
#
# Once you're done here, go to
# http://www.gnu.org/software/make/manual/make.html
# to learn SOOOO much more.
@dergachev
dergachev / GIF-Screencast-OSX.md
Last active Apr 9, 2021
OS X Screencast to animated GIF
View GIF-Screencast-OSX.md

OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Screencapture GIF

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application:

View 20111011_SteveYeggeGooglePlatformRant.md

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

@simonista
simonista / .vimrc
Last active Apr 7, 2021
A basic .vimrc file that will serve as a good template on which to build.
View .vimrc
" Don't try to be vi compatible
set nocompatible
" Helps force plugins to load correctly when it is turned back on below
filetype off
" TODO: Load plugins here (pathogen or vundle)
" Turn on syntax highlighting
syntax on
@MicBrain
MicBrain / metatags.html
Last active Apr 6, 2021
The list of useful meta tags used in HTML5 documents.
View metatags.html
<html>
<head>
<!--Recommended Meta Tags-->
<meta charset="utf-8">
<meta name="language" content="english">
<meta http-equiv="content-type" content="text/html">
<meta name="author" content=”Rafayel Mkrtchyan”>
<meta name="designer" content=”Rafayel Mkrtchyan”>
<meta name="publisher" content=”Rafayel Mkrtchyan”>
@bishboria
bishboria / springer-free-maths-books.md
Last active Apr 6, 2021
Springer made a bunch of books available for free, these were the direct links
@kevinSuttle
kevinSuttle / meta-tags.md
Last active Apr 4, 2021 — forked from lancejpollard/meta-tags.md
List of Usable HTML Meta and Link Tags
@brentp
brentp / linear_model.py
Created Apr 10, 2013
calculate t statistics and p-values for coefficients in Linear Model in python, using scikit-learn framework.
View linear_model.py
from sklearn import linear_model
from scipy import stats
import numpy as np
class LinearRegression(linear_model.LinearRegression):
"""
LinearRegression class after sklearn's, but calculate t-statistics
and p-values for model coefficients (betas).
Additional attributes available after .fit()