How To Install TensorFlow on Debian 10 Buster

Install TensorFlow on Debian 10

In this tutorial we will show you how to install TensorFlow on Debian 10. For those of you who didn’t know, TensorFlow is a free and open source platform for machine learning built by Google. It is used by a number of organizations including Twitter, PayPal, Intel, Lenovo, and Airbus. TensorFlow can be installed system-wide, in a Python virtual environment or as a Docker container using pip.

This article assumes you have at least basic knowledge of Linux, know how to use the shell, and most importantly, you host your site on your own VPS. The installation is quite simple and assumes you are running in the root account, if not you may need to add ‘sudo’ to the commands to get root privileges. I will show you through the step by step installation TensorFlow on a Debian 10 (Buster) server.

Install TensorFlow on Debian 10 Buster

Step 1. Before we install any software, it’s important to make sure your system is up to date by running these following apt commands in the terminal:

Step 2. Installing Python 3 and venv.

Install Python and Python venv using following command:

To verify that Python 3 is installed on your system, type:

Step 3. Creating Virtual Environment.

Create a new directory for the TensorFlow project and cd into it:

Once inside the directory, we run the following command to create the virtual environment:

To start using this virtual environment, you need to activate it by running the activate script:

Step 4. Installing TensorFlow on Debian 10.

TensorFlow installation requires pip version 19 or higher. Run the following command to upgrade pip to the latest version:

Install the TensorFlow package:

Once the installation is complete, verify the installation use the following command:

Congratulation’s! You have successfully installed TensorFlow. Thanks for using this tutorial for installing TensorFlow on your Debian 10 Buster system. For additional help or useful information, we recommend you to check the official TensorFlow website.

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