karpathy

"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.

@karpathy
"""

import os       # os.path.exists
import math     # math.log, math.exp

remojansen

function logClass(target: any) {
 
  // save a reference to the original constructor
  var original = target;
 
  // a utility function to generate instances of a class
  function construct(constructor, args) {
    var c : any = function () {
      return constructor.apply(this, args);
    }

nolanlawson

// Promise.all is good for executing many promises at once
Promise.all([
  promise1,
  promise2
]);

// Promise.resolve is good for wrapping synchronous code
Promise.resolve().then(function () {
  if (somethingIsNotRight()) {
    throw new Error("I will be rejected asynchronously!");

yoavniran

The Ultimate Unit Testing Cheat-sheet

---

• Sinon Chai
• Chai
• Sinon

gbuesing

UPDATE a fork of this gist has been used as a starting point for a community-maintained "awesome" list: machine-learning-with-ruby Please look here for the most up-to-date info!

Resources for Machine Learning in Ruby

Gems

• liblinear-ruby: Ruby interface to LIBLINEAR using SWIG

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

metaskills

module Rack
  class ZombieShotgun
    
    ZOMBIE_AGENTS = [
      /FrontPage/,
      /Microsoft Office Protocol Discovery/,
      /Microsoft Data Access Internet Publishing Provider/
    ].freeze

    ZOMBIE_DIRS = ['_vti_bin','MSOffice','verify-VCNstrict','notified-VCNstrict'].to_set.freeze