Skip to content

Instantly share code, notes, and snippets.

@davatron5000
davatron5000 / gist:2254924
Created March 30, 2012 20:57
Static Site Generators

Backstory: I decided to crowdsource static site generator recommendations, so the following are actual real world suggested-to-me results. I then took those and sorted them by language/server and, just for a decent relative metric, their Github Watcher count. If you want a heap of other projects (including other languages like Haskell and Python) Nanoc has the mother of all site generator lists. If you recommend another one, by all means add a comment.

Ruby

@JoshuaEstes
JoshuaEstes / 000-Cheat-Sheets.md
Last active May 1, 2024 04:03
Developer Cheat Sheets for bash, git, gpg, irssi, mutt, tmux, and vim. See my dotfiles repository for extra info.
# Setup dir and repo
mkdir underscore-string
cd underscore-string
git init
# Make some files we'll need
touch README.md package.js smart.json
# Add the submodule and checkout the desired branch
git submodule add git://github.com/epeli/underscore.string.git lib/underscore.string
@granoeste
granoeste / EachDirectoryPath.md
Last active June 19, 2024 07:37
[Android] How to get the each directory path.

System directories

Method Result
Environment.getDataDirectory() /data
Environment.getDownloadCacheDirectory() /cache
Environment.getRootDirectory() /system

External storage directories

@PaulKinlan
PaulKinlan / criticalcss-bookmarklet-devtool-snippet.js
Last active April 2, 2024 02:45
CriticalCSS Bookmarklet and Devtool Snippet.js
(function() {
var CSSCriticalPath = function(w, d, opts) {
var opt = opts || {};
var css = {};
var pushCSS = function(r) {
if(!!css[r.selectorText] === false) css[r.selectorText] = {};
var styles = r.style.cssText.split(/;(?![A-Za-z0-9])/);
for(var i = 0; i < styles.length; i++) {
if(!!styles[i] === false) continue;
var pair = styles[i].split(": ");
@cyrilmottier
cyrilmottier / CityBikesContract.java
Last active January 12, 2024 18:04
Using the new Gradle-based Android build system: a second example
package com.cyrilmottier.android.citybikes.provider;
import android.net.Uri;
import com.cyrilmottier.android.avelov.BuildConfig;
/**
* @author Cyril Mottier
*/
public class CityBikesContract {
@chrisbanes
chrisbanes / SystemUiHelper.java
Last active March 2, 2024 18:57
SystemUiHelper
/*
* Copyright (C) 2014 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
@jcraig77
jcraig77 / idle.py
Created January 13, 2015 16:08
A python script that monitors idle time on a Windows machine. After the idle threshold is hit, windows media player is started and it plays a playlist. After the playlist is finished or when the operating system is no longer idle, the windows media player is killed.
''' A python script that monitors idle time on a Windows machine.
After the idle threshold is hit, windows media player is started
and it plays a playlist. After the playlist is finished or when the
operating system is no longer idle, the windows media player is killed. '''
from ctypes import Structure, windll, c_uint, sizeof, byref
import subprocess
import time
# how long before the playlist should begin
@miketsprague
miketsprague / DeviceRaisedToEarListener.swift
Created November 3, 2015 18:47
Swift class that lets you know when the user's device was raised to their ear
import Foundation
import CoreMotion
// Warning: This class assumes no one else is currently using the CMMotionManager.
class DeviceRaisedToEarListener: NSObject {
private let deviceQueue = NSOperationQueue()
private let motionManager = CMMotionManager()
private var vertical: Bool = false
private(set) var isRaisedToEar: Bool = false {

A Few Useful Things to Know about Machine Learning

The paper presents some key lessons and "folk wisdom" that machine learning researchers and practitioners have learnt from experience and which are hard to find in textbooks.

1. Learning = Representation + Evaluation + Optimization

All machine learning algorithms have three components:

  • Representation for a learner is the set if classifiers/functions that can be possibly learnt. This set is called hypothesis space. If a function is not in hypothesis space, it can not be learnt.
  • Evaluation function tells how good the machine learning model is.
  • Optimisation is the method to search for the most optimal learning model.