Linux Tactic

Easy Steps to Install TensorFlow on Ubuntu and Pop!_OS

Are you interested in learning how to install TensorFlow on Linux? TensorFlow is a popular open-source platform for machine learning used by data scientists and developers.

If you’re looking to run TensorFlow on your Ubuntu or Pop!_OS machine, we’ve got you covered.

Installing TensorFlow on Ubuntu Linux

Enabling Universe Repository

The Universe repository holds community-maintained packages that arent part of the main Ubuntu software repository. Since TensorFlow is not included in the default Ubuntu repository, we must ensure that the Universe repository is enabled.

To do this, follow these simple steps:

1. Open your terminal and type the command below:

sudo add-apt-repository universe

2. Then you’ll need to update your package list:

sudo apt-get update

Now that youve enabled the Universe repository let’s set up your Python development environment.

Setting up Python development environment

Ubuntu comes with Python pre-installed, but we need to make sure that it’s updated to the latest version. Run the following command in your terminal to update Python:

sudo apt-get install python3-dev python3-pip python3-venv

Getting Pip

Pip is a package manager for Python. It’s a tool used to install packages written in Python.

We’ll need this to install TensorFlow. To install Pip, you can run the following command in your terminal:

sudo apt-get install python3-pip

Setting up Python virtual environment

Python virtual environment is a tool that allows you to create an isolated environment for Python projects, which helps to avoid conflict between the dependencies of different projects. To create a virtual environment for TensorFlow, follow these steps:


Create a directory for your virtual environment:

mkdir my_tensorflow

2. Create a Python virtual environment:

python3 -m venv my_tensorflow

3. Activate the virtual environment:

source my_tensorflow/bin/activate

Installing TensorFlow

Now that weve set up the virtual environment, we can proceed with installing TensorFlow. To do that, run the following command:

pip install –upgrade tensorflow

This command will download and install the latest version of TensorFlow on your system. Once the installation is done, you can start developing with TensorFlow on your Ubuntu machine.

Installing TensorFlow on Pop!_OS

Installing on Pop!_OS is easier. First, we need to install the required dependencies:

sudo apt-get install python3-dev python3-pip

Then, we can install TensorFlow with the following command:

pip3 install tensorflow

This command installs the latest version of TensorFlow for Python 3.


As you can see, installing TensorFlow on Linux can be done in a few simple steps. Ubuntu and Pop!_OS are two of the most popular Linux distributions, and both provide a straightforward way to install TensorFlow on your machine.

With TensorFlow, you can start building and experimenting with machine learning models and algorithms. We hope this tutorial has been helpful in guiding you through the installation process, happy coding!

Wrapping up

In this article, we’ve discussed how to install TensorFlow on Ubuntu and Pop!_OS, two popular Linux distributions. However, before we finish this tutorial, there are a few more topics to cover to ensure your experience with TensorFlow is smooth and fruitful.

Remembering to activate Python virtual environment

When working with a virtual environment, it’s important to activate it before you start working on a project. To activate the virtual environment that we created earlier in the tutorial, run the following command:

source my_tensorflow/bin/activate

You can replace “my_tensorflow” with the name of your virtual environment.

Once activated, your terminal should display the name of your virtual environment before the command prompt.

Resources for learning TensorFlow

TensorFlow is a robust machine learning platform with a wide range of use cases. With that in mind, there are many resources available online to help you get started with TensorFlow and learn more about its capabilities.

Here are a few useful resources to help you get started:

1. TensorFlow’s official website is the best place to start your journey.

It has a user-friendly interface, thorough documentation, and an extensive collection of tutorials, including beginner-level and advanced-level guides. 2.

Coursera is an online learning platform that offers several TensorFlow courses and related subjects, such as machine learning and deep learning. The courses are designed to be interactive, with quizzes, programming assignments, and real-world case studies.

3. PyTorch is another open-source machine learning platform that you can consider learning alongside TensorFlow.

PyTorch is known for its flexibility in model design and intuitive debugging capabilities. 4.

The TensorFlow YouTube channel has a range of video tutorials that cover different aspects of using TensorFlow. The videos are well-designed, informative, and visually appealing.

Troubleshooting issues with modified installations

If you’ve modified your TensorFlow installation or run into an issue with it, there are a few troubleshooting options you can try. Here are some of the most common issues that people face when working with TensorFlow, along with their solutions:


TensorFlow is not installing: If you’re having trouble installing TensorFlow, try updating your machine’s dependencies. Alternatively, attempt to install TensorFlow using the latest version of pip.

2. GPU errors: If you’re using a GPU to accelerate TensorFlow, you might encounter errors during installation or training.

Double-check compatibility with your system and verify that your CUDA (Compute Unified Device Architecture) is up to date. 3.

TensorFlow version conflicts: If you’re running into compatibility issues, ensure that all of your TensorFlow dependencies are of the same version. 4.

Outdated TensorFlow: TensorFlow is updated frequently, and it’s essential to keep up to date with the latest versions as bugs may be discovered after initial releases.


In conclusion, TensorFlow is an open-source machine learning platform that is widely used by data scientists and developers. The goal of this tutorial is to guide you through the process of installing TensorFlow on Ubuntu and Pop!_OS easily.

Activating your virtual environment, consulting resources for learning TensorFlow, and troubleshooting are all elements that can elevate your experience using TensorFlow, which will ultimately benefit you as you learn more about this cutting-edge platform’s capabilities. To summarize, this article outlined the steps to install TensorFlow on Ubuntu and Pop!_OS.

We enabled the Universe repository, set up a Python development environment, got Pip, created a Python virtual environment, and installed TensorFlow. Additionally, we discussed the importance of activating Python virtual environment and provided resources for learning TensorFlow.

Lastly, we offered troubleshooting advice for any issues that may arise. With this knowledge, you can easily install TensorFlow on your Linux machine and begin exploring its capabilities in machine learning.

Remember to stay up to date, be persistent, and keep learning!

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