ryanswanstrom

import urequests as requests

#common functions
def mb_safe(func):
    def _wrapper(*args, **kwargs):
        try:
            return func(*args, **kwargs)
        except Exception as e:
            print('===== mb_safe: ' + str(e))
            return ''

ryanswanstrom

using System;
using System.Collections.Generic;
using System.Linq;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

namespace URLCall
{
    class Program

ryanswanstrom

1. Create an Ubuntu VM in either Azure or AWS or Digital Ocean or somewhere
2. Open port for the VM on port number 19132. (In Azure, in the Network Security Group, add an Inbound security rule)
3. remote connect to the VM (Putty will work for this)

sudo apt-get update
sudo apt-get install default-jre

wget http://ci.mengcraft.com:8080/job/nukkit/lastSuccessfulBuild/artifact/target/nukkit-1.0-SNAPSHOT.jar
mv nukkit-1.0-SNAPSHOT.jar nukkit.jar

ryanswanstrom

http://www.uis.unesco.org/das/api/countries/?region=ALL

http://www.uis.unesco.org/das/api/countries/?code=40500&category=EDULIT_DS&indicators=FEP_5_A,MEP_5_A&fromyear=2008&toyear=2013&mostrecent=false

ryanswanstrom

ryanswanstrom

ryanswanstrom

ryanswanstrom

ryanswanstrom

from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.ensemble import ExtraTreesClassifier
from sklearn import cross_validation
import csv_io as csv
import llfun as logloss
import numpy as np

def main():
    #read in  data, parse into training and target sets

ryanswanstrom

#!/usr/bin/env python

from sklearn.ensemble import RandomForestClassifier
import csv_io
import scipy


def main():
    #read in the training file
    train = csv_io.read_data("train.csv")