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"a4s_employee_full_name"=>
  "\x04\bo:\eRepresentableDataValue\b:\v@fieldo:!EmployeeFullNameBuiltInField\x00:\f@recordo:\rEmployee\x10:\x10@attributeso:\x1FActiveRecord::AttributeSet\x06;\no:$ActiveRecord::LazyAttributeHash\n:\v@types}\x10I\"\aid\x06:\x06ETo:?ActiveRecord::ConnectionAdapters::PostgreSQL::OID::Integer\t:\x0F@precision0:\v@scale0:\v@limit0:\v@rangeo:\nRange\b:\texclT:\nbeginl-\a\x00\x00\x00\x80:\bendl+\a\x00\x00\x00\x80I\"\x0Fcreated_at\x06;\x0ETU:JActiveRecord::AttributeMethods::TimeZoneConversion::TimeZoneConverter[\t:\v__v2__[\x00[\x00o:@ActiveRecord::ConnectionAdapters::PostgreSQL::OID::DateTime\b;\x100;\x110;\x120I\"\x0Fupdated_at\x06;\x0ETU;\x18[\t;\x19[\x00[\x00@\x15I\"\fuser_id\x06;\x0ET@\fI\"\x1Aineligible_for_rehire\x06;\x0ETo: ActiveRecord::Type::Boolean\b;\x100;\x110;\x120I\"\euntracked_prior_tenure\x06;\x0ET@\fI\"\ttags\x06;\x0ETo:=ActiveRecord::ConnectionAdapters::PostgreSQL::OID::Array\a:\r@subtypeo:\x1DActiveRecord::Type::Text\b;\x100;\x110;\x120:\x0F@delimiterI\"\x06,\x06;\x0ET

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# Split the data into training and test sets
X_train, X_test, y_train, y_test = train_test_split(
    data_words, data_plant_types, test_size=0.33, random_state=42)

# Build a neural network
network = input_data(shape=[None, len(data_words[0])])
network = fully_connected(network, 2048, activation='relu')
network = fully_connected(
    network, len(data_plant_types[0]), activation='softmax')

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set nocompatible              " be iMproved, required
filetype off                  " required

" set the runtime path to include Vundle and initialize
set rtp+=~/.vim/bundle/Vundle.vim
call vundle#begin()
" alternatively, pass a path where Vundle should install plugins
"call vundle#begin('~/some/path/here')

" let Vundle manage Vundle, required

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set macligatures
set guifont=Fira\ Code:h12

highlight ColorColumn ctermbg=magenta
call matchadd('ColorColumn', '\%81v', 120)

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#!/bin/sh

case $1 in
  post)
    rmmod i2c_hid
    modprobe i2c_hid
    ;;
esac

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#!/bin/sh
#
# Check to make sure we're not trying to commit debugging code

COMMIT_OK=true

# Find all staged files with appropriate file types (Ruby, Javascript, Vue) 
STAGED_MATCHING_FILENAMES=$(git diff --cached --name-only | grep -E '\.js$|.vue|.rb$')

# Loop over all of the files

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module module_name(signal_a, signal_b);
  input [7:0] signal_a;
  output signal_b;
endmodule

parameter n = 32;

integer k;
for (k = 0; k < n; k + 1)
begin

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function crossed_boundary(current_posn, next_position, direction, segments)



function find_boundaries_crossed(z, segments, min, direction)
  boundaries_crossed = 0
  current_posn = min - 1.5 * DELTA
  bool checking = true
  while(checking)
    next_posn = current_posn + 1

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Boulder Tubing Guide

During the summer, people go tubing down Boulder Creek. To be fun, it has to be just right: enough water flowing, hot enough, and mostly sunny.

Objective: Build an application that lets the user know if it's a good day to go tubing. Implement it however you'd like using. Preferably Ruby on Rails for the backend/API, but beyond that whatever stack you feel is appropriate.

The goal is to demonstrate general competency, and comfort developing an open-ended application. Take about an hour. Since that's not much time, it's fine to describe unfinished parts with what you'd have liked to do.

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# Convert to smaller, monochrome
convert source.jpg -monochrome -resize 320x240 output.jpg
# Convert to gray samples
convert output.jpg gray:output.gray

# Convert back from monchrome samples to jpg (unnecessary)
convert -size 320x240 -depth 8 output.gray rebuild.jpg

# Convert monchrome JPG to RGB colorspace
convert rebuild.jpg -colorspace sRGB -type truecolor rebuild.jpg