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sentences = []
labels = []
with open("/text.csv", 'r') as csvfile:
  csvfile.readline()
  for line in csvfile.readlines():
    row = line.split(',')
    labels.append(row[0])
    sentence = row[1].split()
    sentences.append(' '.join([w for w in sentence if not w in stop_words]))

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version: "3"

networks:
 kong-net:
  driver: bridge

services:

  #######################################
  # Postgres: The database used by Kong

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First, install the following libraries:

$ brew install unixodbc
$ brew install freetds --with-unixodbc

FreeTDS should already work now, without configuration:

$ tsql -S [IP or hostname] -U [username] -P [password]
locale is "en_US.UTF-8"

locale charset is "UTF-8"

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#!/bin/bash

# install CUDA Toolkit v9.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb)
CUDA_REPO_PKG="cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb"
wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
sudo apt-get update
sudo apt-get -y install cuda-9-0

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yum groupinstall "Development Tools"
yum install kernel-devel kernel-headers dkms
yum install pciutils
lspci -nn | grep VGA # to check your NVIDIA product version
yum update
sudo sh NVIDIA-Linux-x86_64-340.32.run --kernel-source-path /usr/src/kernels/3.10.0-123.6.3.el7.x86_64

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In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm

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# configure aws credentials while on corporate network
function aws_config_work(){
   # assumes $WORK_AWS_ACCESS_KEY, $WORK_AWS_SECRET_ACCESS_KEY, $WORK_AWS_DEFAULT_REGION, $CA_PATH
   # are user or system evironment variables

   # environment variables are UPPERCASE even in git bash
   export AWS_ACCESS_KEY_ID=$WORK_AWS_ACCESS_KEY
   export AWS_SECRET_ACCESS_KEY=$WORK_AWS_SECRET_ACCESS_KEY
   export AWS_DEFAULT_REGION=$WORK_AWS_DEFAULT_REGION
   export AWS_CA_BUNDLE=$CA_PATH

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# configure proxy for git while on corporate network
# From https://gist.github.com/garystafford/8196920
function proxy_on(){
   # assumes $USERDOMAIN, $USERDNSDOMAIN, $CA_PATH
   # are existing Windows system-level environment variables

   # assumes $PROXY_SERVER, $PROXY_PORT
   # are existing Windows current user-level environment variables (your user)

   # environment variables are UPPERCASE even in git bash

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#!/bin/bash

# install CUDA Toolkit v8.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-get update
sudo apt-get -y install cuda