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Virtual machines for data science how to install - Windows


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How-to install VirtualBox and Vagrant for Linux to use Virtual Machines for data science on Windows.

Published in: Data & Analytics
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Virtual machines for data science how to install - Windows

  1. 1. Instruction for installing the VirtualBox and Vagrant For Windows OS
  2. 2. Introduction This tutorial will show you how to install VirtualBox and Vagrant, which will allow you to use virtual machines for data science
  3. 3. Hardware and Software requirements You should use a machine with the following minimum hardware requirements: ➔ 3.5 GB free disk space ➔ 2.5 GB (4+ GB preferred) ➔ Any recent Intel or AMD multicore processor should be sufficient. We support the following Operating Systems: ➔ 64-bit (preferred) Windows 7 or later ➔ 32-bit Windows 7 or later
  4. 4. First step: Installing the VirtualBox ➔ Download latest VirtualBox for Windows host here https://www. ➔ Go into the “Downloads” folder. Double-click to install VirtualBox ➔ Go through the default options here (click Next three times). Then OK and Install. ➔ Wait while installation is running. ➔ When the installation is complete, you have the option of starting VirtualBox immediately. Leave that and click Finish. ➔ And there you are in VirtualBox. If you have an error when attempting to start VirtualBox please see the Errors manual
  5. 5. Second step: Installing Vagrant ➔ Go to the page ➔Choose Windows Universal (32 and 64-bit) and download vagrant_1.7.4 file. ➔ Go to My Downloads folder. Double click to Vagrant_1.7.4.msi. ➔ Install Vagrant with default options. For this click Next, Accept the license term, Next, Next and Install. ➔ It does take a few minutes for Vagrant installation. Click Finish. ➔ Now you have a message that you must restart your computer, and then all will be ready.
  6. 6. Installation and usage of virtual machines If all above steps run successfully, you are ready to install and use the virtual machine. Please see “How to install and use” presentation to get you started with virtual machine of your choice (Python or Spark).
  7. 7. Thank you for attention! Virtual Machines by