philippbosch

on alfred_script(q)
	tell application "iTerm"
		activate
	
		try
			set _term to last terminal
		on error
			set _term to (make new terminal)
		end try
	

cboettig

library(Rmpi)
 
## load the packages we'll need
RLIBS="~/R/x86_64-redhat-linux-gnu-library/2.13"
.libPaths(c(RLIBS, .libPaths()))
 
### Direct RMPI way:
mpi.spawn.Rslaves(nslaves=15)
slavefn <- function() { print(paste("Hello from", foldNumber)) }
mpi.bcast.cmd(foldNumber <- mpi.comm.rank())

amcclosky

#!/bin/sh

# usage: mkramdisk 1024 ~/scratch

function mkramdisk() {
  ramfs_size_mb=$1
  mount_point=$2
  ramfs_size_sectors=$((${ramfs_size_mb}*1024*1024/512))
  ramdisk_dev=`hdid -nomount ram://${ramfs_size_sectors}`
  newfs_hfs -v 'ram disk' ${ramdisk_dev}

halpo

################################################################################
# Copyright 2011
# Andrew Redd
# 11/23/2011
#
# Description of File:
# Makefile for knitr compiling
# 
################################################################################
all:pdf  # default rule DO NOT EDIT

fonnesbeck

Horizons in Probabilistic Programming and Bayesian Analysis

Representations:

• Hierarchical models
• Hidden Markov models
• Graphical models
• Non-parametric Bayes (distributions over functions)

Inference Approaches:

cjw85

"""
Reimplementation of nanonet using keras.

Follow the instructions at
https://www.tensorflow.org/install/install_linux
to setup an NVIDIA GPU with CUDA8.0 and cuDNN v5.1.

virtualenv venv --python=python3
. venv/bin/activate
pip install numpy

robertsdionne

#!/usr/bin/env bash

# Assuming OS X Yosemite 10.10.4

# Install XCode and command line tools
# See https://itunes.apple.com/us/app/xcode/id497799835?mt=12#
# See https://developer.apple.com/library/mac/documentation/Darwin/Reference/ManPages/man1/xcode-select.1.html
xcode-select --install

genekogan

Instructions for making a Neural-Style movie

The following instructions are for creating your own animations using the style transfer technique described by Gatys, Ecker, and Bethge, and implemented by Justin Johnson. To see an example of such an animation, see this video of Alice in Wonderland re-styled by 17 paintings.

Setting up the environment

The easiest way to set up the environment is to simply load Samim's a pre-built Terminal.com snap or use another cloud service like Amazon EC2. Unfortunately the g2.2xlarge GPU instances cost $0.99 per hour, and depending on parameters selected, it may take 10-15 minutes to produce a 512px-wide image, so it can cost $2-3 to generate 1 sec of video at 12fps.

If you do load the

djhocking

one <- seq(1:10)
two <- rnorm(10)
three <- runif(10, 1, 2)
four <- -10:-1

df <- data.frame(one, two, three)
df2 <- data.frame(one, two, three, four)

str(df)

sbalnojan

import s3fs
import pickle
import json
import numpy as np

BUCKET_NAME = "my-bucket"

# definitions, keras/tf/... imports...

if __name__ == "__main__":