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PRINT 'THE SERVER IS ' + @@SERVERNAME
--select db_name()
PRINT 'THE DATABASE IS ' + db_NAME() 
PRINT ''
GO

USE [master]

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#/usr/bin/python

# http://exploreflask.com/en/latest/views.html
# https://stackoverflow.com/questions/51691730/flask-middleware-for-specific-route
# https://dev.to/rhymes/logging-flask-requests-with-colors-and-structure--7g1

import logging
from logging.handlers import RotatingFileHandler
from flask import Flask, request, jsonify
from time import strftime

asw456

For anyone who is interested, here's a case study on serialization of scala closures that may or may not have been the result of a lengthy and passionate discussion about what you can and can't serialize and why it's necessary to generate a closure with a generating function if you want to use it in Spark

import java.io.{ByteArrayOutputStream, ObjectOutputStream, NotSerializableException}

object Temp {

  def main(args: Array[String]): Unit = {

    def serialize(value: Any): Array[Byte] = {

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Initialize

gitflow	git
git flow init	git init
	git commit --allow-empty -m "Initial commit"
	git checkout -b develop master

Connect to the remote repository

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"""Character based language modeling with multi-layer GRUs.

To train the model:

  python3 in_graph_char_rnn.py --mode training \
      --logdir path/to/logdir --corpus path/to/corpus.txt

To generate text from seed words:

  python3 in_graph_char_rnn.py --mode sampling \

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function gnn (cases, wide, tall, population, iterations, error_fn, error_thresh) {
	var inputs = cases[0][0].length;
	var outputs = cases[0][1].length;
	// declare net, provide input layer
	var net = [new Array(inputs)];
	// create input neurons in input layer
	for (var i = 0; i < inputs; i++) 
		net[0][i] = {output: 0}
	// create hidden layers
	for (var x = 0; x < wide; x++) {

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import torch
from torch.autograd import Variable
import torch.nn as nn


class Bottleneck(nn.Module):
    cardinality = 32  # the size of the set of transformations

    def __init__(self, nb_channels_in, nb_channels, nb_channels_out, stride=1):
        super().__init__()

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// Based on tinrtgu's Python script here:
// https://www.kaggle.com/c/avazu-ctr-prediction/forums/t/10927/beat-the-benchmark-with-less-than-1mb-of-memory 
package main

import (
    "encoding/csv"
    "os"
    "strconv"
    "hash/fnv"
    "math"

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##Google Interview Questions: Product Marketing Manager

• Why do you want to join Google? -- Because I want to create tools for others to learn, for free. I didn't have a lot of money when growing up so I didn't get access to the same books, computers and resources that others had which caused money, I want to help ensure that others can learn on the same playing field regardless of their families wealth status or location.
• What do you know about Google’s product and technology? -- A lot actually, I am a beta tester for numerous products, I use most of the Google tools such as: Search, Gmaill, Drive, Reader, Calendar, G+, YouTube, Web Master Tools, Keyword tools, Analytics etc.
• If you are Product Manager for Google’s Adwords, how do you plan to market this?
• What would you say during an AdWords or AdSense product seminar?
• Who are Google’s competitors, and how does Google compete with them? -- Google competes on numerous fields: --- Search: Baidu, Bing, Duck Duck Go

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import java.io.IOException;
import java.nio.ByteBuffer;
import java.util.*;
import org.apache.cassandra.db.IColumn;
import org.apache.cassandra.thrift.*;
import org.apache.cassandra.hadoop.*;
import org.apache.cassandra.utils.ByteBufferUtil;
import org.apache.hadoop.conf.*;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.*;