wolfv

import sys
CONDA_PATH = '/home/wolfv/Programs/conda/'

sys.path.insert(0, CONDA_PATH)
# orig, sys.path = sys.path, [CONDA_PATH]
# import conda
# from tests import helpers
# sys.path = orig + [CONDA_PATH]

# i, r = helpers.get_index_r_1()

beesandbombs

// gif by dave aka @beesandbombs :)

int[][] result;
float t, c;

float ease(float p) {
  return 3*p*p - 2*p*p*p;
}

float ease(float p, float g) {

karpathy

"""
A bare bones examples of optimizing a black-box function (f) using
Natural Evolution Strategies (NES), where the parameter distribution is a 
gaussian of fixed standard deviation.
"""

import numpy as np
np.random.seed(0)

# the function we want to optimize

denilsonsa

karpathy

"""
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)

nicoptere

/*
from : http://en.wikipedia.org/wiki/Mersenne_twister
*/
let MT
let index
class PRNG {
  static setSeed(seed) {
    // Create a length 624 array to store the state of the generator
    MT = new Uint32Array(624)
    index = 0

xem

<!-- solution 1, 117b, inspired by http://www.p01.org/releases/140bytes_music_softSynth/ -->
<button onclick="new Audio('data:audio/wav;base64,UklGRl9vT19XQVZFZm10IBAAAAABAAEAQB8AAEAfAAABAAgAZGF0YU'+Array(1e3).join(123)).play()">Beep</button>

<!-- Solution 2, 107b, inspired by http://xem.github.io/chip8/c8.html -->
<button onclick="o=(A=new AudioContext()).createOscillator();o.connect(A.destination);o.start(0);setTimeout('o.stop(0)',500)">Boop</button>

gre

JS1K Boilerplate

Build tools

Install tools

npm install

zacstewart

import os
import numpy
from pandas import DataFrame
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.pipeline import Pipeline
from sklearn.cross_validation import KFold
from sklearn.metrics import confusion_matrix, f1_score

NEWLINE = '\n'

iamatypeofwalrus

What

Roll your own iPython Notebook server with Amazon Web Services (EC2) using their Free Tier.

What are we using? What do you need?

• An active AWS account. First time sign-ups are eligible for the free tier for a year
• One Micro Tier EC2 Instance
• With AWS we will use the stock Ubuntu Server AMI and customize it.
• Anaconda for Python.
• Coffee/Beer/Time