mrocklin

leeper

# uses dev version of 'waffle'
# devtools::install_github("leeper/waffle@patch-1")
library("waffle")
library("extrafont")

# population
set.seed(1)
N <- 900L
p <- c("Small Group 1" = 30, "Big Group 1" = 420, "Small Group 2" = 30,"Big Group 2" = 420)
glyph <- c("male", "female")[sample(1:2, N, TRUE)]

AustinRochford

jkleint

#!/usr/bin/env python
"""
Example of using Keras to implement a 1D convolutional neural network (CNN) for timeseries prediction.
"""

from __future__ import print_function, division

import numpy as np
from keras.layers import Convolution1D, Dense, MaxPooling1D, Flatten
from keras.models import Sequential

tomokishii

#
#  mnist_cnn_bn.py   date. 5/21/2016
#                    date. 6/2/2017 check TF 1.1 compatibility
#

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import os

mrocklin

AustinRochford

springcoil

ncray

## There's a dependency on https://github.com/JohnLangford/vowpal_wabbit
library(plyr)
library(dplyr)
library(magrittr)
library(pander)

panderOptions('table.split.table', Inf)

LOW_MEAN <- .4
HIGH_MEAN <- .6

johnynek

import scala.collection.immutable.Queue

object Median {
  sealed trait State {
    def count: Long
    def add(item: Long): State
    def median: Long
  }
  case class Start(window: Queue[Long], max: Int, countInt: Int) extends State {
    def count = countInt