NoRaincheck

Smoothies

• Frozen Berries
• Thickened Cream

Vegetables

• Any frozen variety (check carbs)

Eggs (Any)

EderSantana

Code for Keras plays catch blog post

Train

python qlearn.py

Test

1. Generate figures

gabrieleangeletti

import tensorflow as tf
import numpy as np
import os

import zconfig
import utils


class RBM(object):

jkeirstead

Zulko

#
# This Python script makes a summary of a football game by cutting
# the video around the 10 % loudest moments, which generally 
# include the goals and other important events.
# For more details, see this blog post:
# http://zulko.github.io/blog/2014/07/04/automatic-soccer-highlights-compilations-with-python/
#
# LICENCE: Creative Commons 0 - Public Domain
# I, the author of this script, wave any rights and place this work in the public domain.
#

whoisjake

$script = <<SCRIPT
apt-get update --fix-missing
apt-get install -y python-software-properties
add-apt-repository ppa:terry.guo/gcc-arm-embedded
apt-get update
apt-get install -y build-essential
apt-get install -y gcc-arm-none-eabi
apt-get install -y dfu-util
apt-get install -y git-core

jvns

A lot of these are outright stolen from Edward O'Campo-Gooding's list of questions. I really like his list.

I'm having some trouble paring this down to a manageable list of questions -- I realistically want to know all of these things before starting to work at a company, but it's a lot to ask all at once. My current game plan is to pick 6 before an interview and ask those.

I'd love comments and suggestions about any of these.

I've found questions like "do you have smart people? Can I learn a lot at your company?" to be basically totally useless -- everybody will say "yeah, definitely!" and it's hard to learn anything from them. So I'm trying to make all of these questions pretty concrete -- if a team doesn't have an issue tracker, they don't have an issue tracker.

I'm also mostly not asking about principles, but the way things are -- not "do you think code review is important?", but "Does all code get reviewed?".

sklam

import json
from pprint import pprint as pp

import numpy as np
from numba import autojit, typeof, int32

INF = float('inf')

@autojit
def jenks_matrics_init(data, n_classes, ):

llimllib

import json
from pprint import pprint as pp

def jenks_matrices_init(data, n_classes):
    #fill the matrices with data+1 arrays of n_classes 0s
    lower_class_limits = []
    variance_combinations = []
    for i in xrange(0, len(data)+1):
        temp1 = []
        temp2 = []