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Arthur Kim kimdwkimdw

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Running & Learning
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@epicure
epicure / llama2.html
Created July 26, 2023 17:06
A pure JavaScript port of @karpathy's llama2.c
<!DOCTYPE html>
<meta charset="utf-8">
<style>
body {
padding: 1em;
}
label, button {
margin: 0.5em;
}
input {
@navsing
navsing / clubhouse.swift
Created February 11, 2021 21:22
Recreating ClubHouse in SwiftUI with Dark Mode
//
// Clubhouse.swift
// Playground
//
// Created by Nav Singh on 2/11/21.
//
import SwiftUI
struct Clubhouse: View {
@gnuton
gnuton / Mixamo.js
Last active January 22, 2024 07:29
Script which downloads all mixamo animations for one character.
// Mixamo Animation downloadeer
//
// Author: Antonio Aloisio <gnuton@gnuton.org>
// Contributions: kriNon
//
// The following script make use of mixamo2 API to download all anims for a single character that you choose.
// The animations are saved with descriptive long names instead of the short ones used by default by mixamo UI.
//
// This script has been written by gnuton@gnuton.org and the author is not responsible of its usage
//
@MrTrustor
MrTrustor / clean-docker-for-mac.sh
Last active November 21, 2023 11:38
This script cleans the Docker.qcow2 file that takes a lot of disk space with Docker For Mac. You can specify some Docker images that you would like to keep.
#!/bin/bash
# Copyright 2017 Théo Chamley
# Permission is hereby granted, free of charge, to any person obtaining a copy of
# this software and associated documentation files (the "Software"), to deal in the Software
# without restriction, including without limitation the rights to use, copy, modify, merge,
# publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons
# to whom the Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all copies or
@karpathy
karpathy / pg-pong.py
Created May 30, 2016 22:50
Training a Neural Network ATARI Pong agent with Policy Gradients from raw pixels
""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym
# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward
@trustin
trustin / smi2ass.py
Last active January 24, 2023 03:25
smi2ass.py - converts a SAMI (.smi) subtitle file to the SubStationAlpha (.ass) format.
#!/usr/bin/env python2
# -*- coding: UTF-8 -*-
# Note: A newer version of this script is located at https://github.com/trustin/smi2ass
#
# Copyright (C) 2018 Trustin Heuiseung Lee and other contributors
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
@karpathy
karpathy / min-char-rnn.py
Last active June 28, 2024 06:13
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)
@acuros
acuros / daum.js
Last active July 30, 2018 02:22
Daum Login
var daumlogin = {};
var daum = {}
daum.Browser = {ua:'mozilla/5.0 (windows nt 6.1; wow64) applewebkit/537.11 (khtml, like gecko) chrome/23.0.1271.95 safari/537.11'}
daum.Event = {}
daum.Event.addOrderEvent = (function () {
var a = {};
return function (f, e, g, b) {
var h = null,
c, d;
if (!f) {
@lifthrasiir
lifthrasiir / crypto.md
Last active November 14, 2023 07:10
High-level understanding of cryptography

고수준에서 암호학 이해하기

이 글은 메아리 저널에 쓸 목적으로 한동안 작업하던 글입니다. 메아리 특유의 디자인(...)이 싫다면 여기로 링크하셔도 됩니다. 어느 쪽이든간에 의견은 이 아래의 코멘트 란 또는 메아리에 기재되어 있는 메일 주소를 써 주시면 감사하겠습니다. --lifthrasiir

암호학을 사용하는 많은 시스템은 세부적으로 무슨 알고리즘을 쓰는지보다는 그 알고리즘들이 어떻게 연결되어 있는지, 즉 구조가 실제 안전성에 더 큰 영향을 미친다. 따라서 구조와 그 구조를 이루는 빌딩 블럭을 아는 것이 중요한데, 여기에서는 이러한 암호학적 빌딩 블럭과 함께 블럭들이 어떻게 쓰여서 더 큰 구조를 만드는지를 알아 본다.

Key Exchange

키 교환. 두 사람만이 알 수 있는 새로운 키를 만든다. 이 과정이 끝나도 상대방이 내가 아는 사람인진 알 수 없지만 적어도 상대방과 내가 같은 키를 가지고 있다는 건 확신할 수 있다.