musically-ut

#!/bin/sh

PAT='#\s*NO(.)?GIT'
git diff --cached --name-only | \
    xargs egrep -i --color --with-filename -n "$PAT" && echo "Found '"$PAT"' in code about to be committed. Rejecting commit." && exit 1

# Exit with error code zero if all went well.
exit 0

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

jiahao

Isaddo

/*
  Go on your labels page (https://github.com/user/repo/labels)

  Edit the following label array
  or
  Use this snippet to export github labels (https://gist.github.com/MoOx/93c2853fee760f42d97f)
  and replace it

  Paste this script in your console
  Press Enter!!

moreka

Broadcast Code Readme

This project is Python2-compatible and have issues while running with python 3. So please use Python2 (We used Anaconda's CPython distribution, maybe PyPy would be faster, but I don't even know whether it's OK to move to PyPy)

1. Data Access

All data access related classes are in data package. We suppose there are two SQLite databases, namely db.sqlite3 and links.sqlite3 which are stored on shared memory (/dev/shm) for faster access (they should be copied, in case of vanishing). First DB, holds tweets table with following schema:

CREATE TABLE tweets (user_id integer, tweet_time integer);

musically-ut

require 'graph';
require 'os';

function displayGraph(g, forward)
    local imgFile = os.tmpname() .. '.png'
    local dag = g.fg
    
    if forward == false then
        dag = g.bg
    end

o-jasper

// ==UserScript==
// @name        Arxiv titlatorizer
// @namespace   Titlatorizer
// @description Replaces the arxiv title with the ... title.
// @include     http://arxiv.org/*
// @include     https://arxiv.org/*
// @version     0.0
// @grant       GM_xmlhttpRequest
// ==/UserScript==
//

wesbos

// paste in your console
    speechSynthesis.onvoiceschanged = function() {
      var msg = new SpeechSynthesisUtterance();
      msg.voice = this.getVoices().filter(v => v.name == 'Cellos')[0];
      msg.text = Object.keys(window).join(' ');
      this.speak(msg);
    };

musically-ut

Scripts to convert datasets from unruly forms to SQLite

The script json2sqlite.py reads files which have one JSON block per new line to be inserted in a database. This has become a rather common dataformat which is easy to incrementally parse. The arguments to the scripts are self explanatory.

Example execution: python json2sqlite.py --gzip aggressive_dedup.json.gz amazon.sqlite reviews

For a more upto date scripts, see: Networks-Leraning/datasets2sqlite.

diegopacheco

How to Install GO Lang on CentOS / Amazon Linux?

sudo wget https://storage.googleapis.com/golang/go1.4.2.linux-amd64.tar.gz
tar -xzf go1.4.2.linux-amd64.tar.gz 
export GOROOT=PATH_WHERE_YOU_EXTRACT_GO
export PATH=$PATH:$GOROOT/bin 
export GOBIN=$GOROOT/bin 
mkdir ~/golang/ 
export GOPATH=~/golang/