What OS Do Data Scientists Prefer And Why?
So, as a new data scientist, you are experimenting with machine learning tools like TensorFlow or PyTorch. Are you curious about What OS Do Data Scientists Prefer And Why? You are excited and about to create your first environment when you pause and consider your operating system. Linux or Windows?
When you ask your coworkers, there are conflicting and vehement responses. Selecting the ideal OS for your project can be challenging. We are all wired to assume that you are a Windows or Mac person from an early age.
If you begin working with advanced software, artificial intelligence, data science, or machine learning, you will discover that most specialists use either Windows or Linux. Which one ought you to pick then? This article should help you realize which OS is ideal for your project and save you some time.
What OS Do Data Scientists Prefer And Why?
I am fairly at ease with the configuration and use Windows + Linux (remote) at home and Mac + Linux (remote) in the office. However, there are so many situations in which you might have preferences regarding the OS.
For instance, if I need to deploy a machine learning model for usage in production, I will unquestionably choose a Linux server; however, if I need to create a presentation with plenty of graphics, I will be more productive working on Mac or Windows. Therefore, the answer is greatly influenced by your everyday tasks.
Why Choose Linux For Data Science And Machine Learning?
A Large And Active Community
Due to its open-source nature, Linux has a sizable contributor community. The Linux community is quite active, and if you need assistance looking for a mistake, there is a vast network available. Libraries and tutorials are in abundant supply. You may find a great introduction to Linux for data science on dagshub.com.
More Fast Computers
Compared to Windows, Linux provides better computing power. Because of this, 90% of all supercomputers run Linux. Data scientists can process vast amounts of data quickly by using Linux. Utilizing NVIDIA Docker is possible with Linux, which is an additional benefit.
Flexibility
The Linux OS provides several software options for carrying out the same function. Compared to Windows, Linux is more feature- and usability-rich. The functionality flexibility of Linux is one of its primary features. It may be run on outdated systems and uses minimal resources to operate.
Free Services
This benefit cannot be disregarded. Linux OS is free. Therefore, by modifying apps to suit your data science needs, you may give back to the Linux community if you’re a data scientist and a supporter of open-source projects. Even the source code can be changed to include new features.
Security
Because of its resilience, Linux is generally more secure than Windows. Because installing apps or executables is difficult, the CLI command line provides more security than Windows. The terminal is simple to use for Linux commands and scripting.
Performance
According to users, Linux performs better than Windows in data transfer commands and application installs. Even with powerful artificial intelligence and Deep Learning, it operates more quickly.
Modularity
Linux is simpler to handle because you can access Super User rights with just one command. Linux makes partitioning considerably simpler as well. Linux OS does have certain drawbacks, though. The software cannot be packaged in a single method, and no standardized desktop environment exists. Furthermore, it has poor gaming support.
Why Is Python So Popular Among Data Scientists?
One of the key factors contributing to Python’s widespread use in scientific and research circles is its user-friendliness and straightforward syntax, which make it easier for those without engineering backgrounds to pick up.
Additionally, it is better suited for rapid prototyping. Python’s success may also be because most online data science and machine learning courses promote it as being user-friendly for beginners.
Python’s versatility has led to most developers referring to it as the Swiss Army Knife of the data science field. It is simple to understand why Python continues to be one of the most in-demand talents among data science and analytics experts, according to these companies.
In addition to the scientific packages developed by academia and industry, deep learning frameworks made available through Python online training, in the opinion of engineers, have made Python tremendously productive and adaptable.
According to Towards Data Science, deep learning Python frameworks have undergone significant evolution since TensorFlow’s debut two years ago. AI involves extensive research, as one developer observed on a forum, yet Python allows one to test a concept with as few as thirty lines of code.
ML scientists favor Python as well in terms of application domains. Developers tended to favor Java regarding areas like creating fraud detection algorithms and network security; yet, because of Python’s extensive library ecosystem, developers chose it for applications like sentiment analysis and natural language processing (NLP).
Conclusion
Did you know What OS Do Data Scientists Prefer And Why? Most data scientists favor Linux over Windows, yet it will depend on your particular case needs. It is more versatile, user-friendly, and capable of handling the volume of data required for a machine learning project without breaking the budget.
Frequently Asked Questions
Which OS suits data scientists the best?
The majority of data scientists in the world prefer Ubuntu. Additionally, it is the most widely used Linux distribution with machine learning features on public clouds.
What motivates data scientists to use Macs?
The fact that most data scientists like Macs, despite their high cost, is a well-known truth. Its compatibility with other data science tools is also taken into account. Macs are robust, resilient, and incredibly competent machines.
Do you recommend Linux for data science?
Because Linux Distro is open source, you can perform your research without spending any money on software, making it the greatest option for data science.
Which OS is most suitable for ML and AI?
Linux. Linux is one of the most often utilized operating systems for machine learning. The complicated installation and configuration procedures demanded by many machine learning software are ideally suited to Linux systems’ open-source nature.
Since childhood, I’ve been fascinated by computer technology, and have experimented with a variety of hardware and software. It was a dream come true to graduate from a renowned university with a degree in computer engineering, which made it possible for me to pursue my dreams swiftly.