Jim Fleming jimfleming

Around 2006-2007, it was a bit of a fashion to hook lava lamps up to the build server. Normally, the green lava lamp would be on, but if the build failed, it would turn off and the red lava lamp would turn on.

By coincidence, I've actually met, about that time, (probably) the first person to hook up a lava lamp to a build server. It was Alberto Savoia, who'd founded a testing tools company (that did some very interesting things around generative testing that have basically never been noticed). Alberto had noticed that people did not react with any urgency when the build broke. They'd check in broken code and go off to something else, only reacting to the breakage they'd caused when some other programmer pulled the change and had problems.

A comparison of Theano with other deep learning frameworks, highlighting a series of low-level design choices in no particular order.

Overview

Differentiation

Differentiation

Symbolic: Theano, CGT; Automatic: Torch, MXNet

Symbolic and automatic differentiation are often confused or used interchangeably, although their implementations are significantly different.

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

The problem to solve

An example problem from the textbook Physics for Scientists and Engineers by Serway and Jewett:

Let's solve this using Symbolism, a C# library for computer algebra and symbolic computation.

Symbol definitions

In all the discussions about ES6 one thing is bugging me. I'm picking one random comment here from this io.js issue but it's something that comes up over and over again:

There's sentiment from one group that Node should have full support for Promises. While at the same time another group wants generator syntax support (e.g. var f = yield fs.stat(...)).

People keep putting generators, callbacks, co, thunks, control flow libraries, and promises into one bucket. If you read that list and you think "well, they are all kind of doing the same thing", then this is to you.

	from tsne import bh_sne
	import numpy as np
	from skimage.transform import resize

	from matplotlib import pyplot as plt

	def gray_to_color(img):
	if len(img.shape) == 2:
	img = np.dstack((img, img, img))
	return img

	#!/bin/bash

	# Run this on This AMI on AWS:
	# https://console.aws.amazon.com/ec2/v2/home?region=us-east-1#LaunchInstanceWizard:ami=ami-b36981d8

	# You should get yourself a fully working GPU enabled tensorflow installation.

	cd ~

	# grab cuda 7.0

	class Panda3d < Formula
	desc "Framework for 3D rendering and game development"
	homepage "https://www.panda3d.org"
	url "https://www.panda3d.org/download/panda3d-1.9.0/panda3d-1.9.0.tar.gz"
	version "1.9.0"
	sha256 "4bcec504d35d64eaaeb93d47be747de460bf582e2b1bf91ed311e0b4fd04cc83"

	depends_on :python => :build

	depends_on :python => :recommended

	#![feature(globs)]

	use std::fmt;
	use std::hash::Hash;
	use Expr::*;
	use MaybeOwned::*;

	// TODO:
	// * multiple dispatch
	// * sorting of symbols