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Many developers and IT professionals working at Fortune 500 companies use a Linux or MacOS distribution. Why Linux? Because most servers run on Linux and provide a wide variety of tools that Windows 11 lacks. Also, if you are concerned about security and privacy, moving to Linux is the right decision. Last month, I've been testing some of these distros using VirtualBox VMs and I'm seriously considering Linux as my primary system.
In this blog, we will learn about a Linux distribution that I have fallen in love with, which supports all kinds of tools needed for your data science experiments and machine learning model training. They are also very easy to use and you can install them in just a few minutes.
we all know about ubuntu, and I think if you are a developer or machine learning engineer, you are using Ubuntu on Windows 11 via WSL. Ubuntu is the most popular Linux distribution out there due to its easy-to-use interface, extensive documentation, and support from a large community.
Ubuntu is a great option for those new to Linux and its repositories are rich in data science libraries and tools, making it easy to set up your development environment. Additionally, it is a stable operating system that provides long-term support, even longer than Windows.
Fedora workstation It is a very mature and popular operating system for developers and programmers. What sets Fedora apart is its dedication to providing the latest software and features, which is crucial for data scientists looking for the latest developments in software tools and libraries.
It's completely free, ad-free, and values your data privacy. Additionally, its strong emphasis on open source values ensures that users have access to a vast ecosystem of free and open source software (FOSS) tools.
Zorin OS It is quickly becoming my favorite operating system due to its ease of installation and pre-installed software. It's particularly easy to use for those transitioning from Windows or macOS, and offers a simple and elegant interface without sacrificing power or functionality.
Zorin OS, being based on Ubuntu, can take advantage of its extensive software repository and support. For data scientists, Zorin OS provides a comfortable and familiar environment while offering the versatility and performance that Linux is famous for.
Pop!_OS is a popular Linux distribution that comes with pre-installed Nvidia GPU drivers. This means you won't have to install anything additional to start training your deep learning model on the GPU. It is quite similar to Zorin OS in terms of ease of use and pre-installed applications.
Pop!_OS is based on Ubuntu but adds its own flair with a streamlined and improved user interface that focuses on productivity and ease of use. I was able to install and start using VSCode for my project in just a few minutes. It's very easy to navigate and comes with tons of customization options.
Manjaro is an easy-to-use Linux distribution based on Arch Linux. Unlike Arch, which is aimed at more experienced users, Manjaro offers all the benefits of Arch Linux, including access to the AUR (Arch User Repository), in a more accessible and easy-to-install package.
Manjaro is known for its rolling release model, which means you receive regular updates and the latest software packages. It is also highly customizable, allowing users to tailor the operating system to their specific needs. Additionally, it provides a wide range of data science libraries and tools that are very important if you want to develop and deploy data science solutions.
Choosing the right Linux distribution for data science depends on personal preferences, specific project requirements, and your comfort level with Linux environments.
Linux differs significantly from Windows and macOS. Therefore, it is recommended to try several stable Linux distributions and choose the one that works best for you. Some professionals prefer Arch, while others prefer Ubuntu. Ultimately, it depends on your personal preferences.
Fedora Workstation, Ubuntu Desktop, Zorin OS, Pop!_OS, and Manjaro are among the best options for data science professionals and each offers unique benefits. Experimenting with one or more of these distributions will help you find the perfect fit for your data science journey.
Abid Ali Awan (@1abidaliawan) is a certified professional data scientist who loves building machine learning models. Currently, he focuses on content creation and writing technical blogs on data science and machine learning technologies. Abid has a Master's degree in technology Management and a Bachelor's degree in Telecommunications Engineering. His vision is to build an artificial intelligence product using a graph neural network for students struggling with mental illness.
