P8H

import dask
import numpy as np
import pandas as pd
import dask.dataframe as ddf

dask_chunks = 20

# Partition the dataframe
slices = [
    np.datetime64(d)

P8H

from IPython.display import HTML
style = "<style>#output-body{display:flex; flex-direction: row;}</style>"
display(HTML(style))

display(SVG('level_0_eval/cg.svg'))
display(SVG('level_0_eval/cg.svg'))

P8H

#!/bin/bash
mkdir /etc/resilio
cd /etc/resilio
wget -N --no-check-certificate https://download-cdn.resilio.com/stable/linux-arm/resilio-sync_arm.tar.gz
tar xvzf resilio-sync_arm.tar.gz
rm resilio-sync_arm.tar.gz
wget -N --no-check-certificate https://gist.githubusercontent.com/P8H/379f5e48a66794311fefd86e74022d54/raw/resilio.conf
cd /etc/init.d/
wget -N --no-check-certificate https://gist.githubusercontent.com/P8H/379f5e48a66794311fefd86e74022d54/raw/resiliod
e

P8H

import org.nd4j.jita.conf.CudaEnvironment;
import org.nd4j.jita.conf.Configuration;

public class TestClass {
    public static void main(String[] args) throws Exception {

        CudaEnvironment.getInstance().getConfiguration().allowMultiGPU(true); //Use all available GPUs
        DataTypeUtil.setDTypeForContext(DataBuffer.Type.HALF); //Use half precision, boost learning up to 200%
        CudaEnvironment.getInstance().getConfiguration()
                .setMaximumDeviceCacheableLength(1024 * 1024 * 1024L)

P8H

import org.deeplearning4j.datasets.fetchers.MnistDataFetcher;
import org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator;
import org.deeplearning4j.nn.api.OptimizationAlgorithm;
import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
import org.deeplearning4j.nn.conf.layers.OutputLayer;
import org.deeplearning4j.nn.conf.layers.RBM;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;

P8H

% synthetic dataset for multiple-instance learning using standard MI assumption.

@relation demo1

@attribute bag_XY {BAGN-1,BAGN-2,BAGP-3}
@attribute bag relational
  @attribute f1 numeric
  @attribute f2 numeric
@end bag

P8H

# Watchdog install script for raspberry pi
# based on http://binerry.de/post/28263824530/raspberry-pi-watchdog-timer
# first think about to update the firmaware: rpi-update
sudo bash
apt-get install watchdog chkconfig

modprobe bcm2708_wdog

echo "WantedBy=multi-user.target" >> /lib/systemd/system/watchdog.service
# http://raspberrypi.stackexchange.com/a/33901

P8H

from multiprocessing.managers import BaseManager

class IPC(BaseManager):
    """Little example how to provide a shutdown() function if you us the serve_forever method
    """""

    _server_object = None  # docs.python.org/3.5/library/multiprocessing.html#multiprocessing.managers.BaseManager

    def __init__(self):
        BaseManager.__init__(self, address=('127.0.0.1', 4000), authkey=b'42')