Best Laptops For Data Science Students: Data Handling And Analysis – Explore the essential factors to consider when buying a laptop for deep learning, machine learning, and data science work.
In today’s rapidly evolving world, the fields of deep learning, machine learning, and data science are becoming extremely popular. Aspiring professionals and enthusiasts in these fields require powerful computing devices to handle complex algorithms and large data sets. If you are planning to buy a laptop for deep learning, machine learning or data science work then you have come to the right place. In this comprehensive guide, we’ll discuss the essential factors to consider and offer top recommendations for every budget.
Best Laptops For Data Science Students: Data Handling And Analysis
The processor is the heart of every computer, and it plays a vital role in deep learning, machine learning, and data science tasks. Look for a laptop with a powerful multi-core processor to ensure smooth performance. We recommend at least an Intel Core i5 or AMD Ryzen 5 processor. However, if your budget allows, choose an Intel Core i7 or AMD Ryzen 7 processor for even better performance.
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Dedicated GPUs are essential for deep learning and machine learning tasks because they speed up the neural network training process. NVIDIA GPUs are highly regarded for their CUDA cores, which significantly improve performance in deep learning tasks. Consider a laptop with at least NVIDIA GeForce GTX 1650 or higher, such as the NVIDIA GeForce RTX 20-series or 30-series.
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8 Laptop Requirements for Data Scientists [Complete Guide]In today’s data-driven world, data scientists play a vital role in analyzing information and Find valuable insights. To do their job… Note: You can find many “best calculators for data science” articles online… but you need to know that most of them have affiliate links. (For example, linking to Amazon.) There’s nothing wrong with that – except for the obvious possibility of bias… There are no affiliate links in this article, and I generally don’t link to products The product I introduce here. Here you’ll read 100% unbiased recommendations, based on my experience and that of my fellow data scientists.
Before going deeper into the topic, let me put right here a short list of the best computers/laptops that I recommend for data science:
Because 99% of the time you use a remote server for all your IT-heavy data projects. (Well, at least, if you’re serious about data science.) So your personal computer will effectively just act as an “interpreter” between the server and yourself.
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I wrote about this in detail in my remote server article (How to Install Python, SQL, R and Bash).
“What we do here is connect to a remote server – type a command and ask the remote server to do the calculation instead of our local computer.”
See, it doesn’t matter how powerful your personal computer is… What matters is the computing power of your remote server.
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Note: If you work for a company, you use their remote server so you don’t have to worry about that either. On the other hand, if you use your own server (for personal data science projects, for example), you can easily increase or decrease its computing power.
Of course, there are better and worse options – but the deciding factors are a little different than what most aspiring data scientists think.
But there are some programs that you should always run locally on your computer. Just a few of these:
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If you’re using a Mac, it’s easy. In my experience, all data science tools work properly in MacOS. (The reason for this is because—spoiler alert—usually Macs are the preferred choice for most data scientists. So most software companies are very interested to ensure their products work well on Macs.)
If you have a Windows computer, my recommendation is to use Windows 10 (or higher) – and also install Linux (Ubuntu) on it. (Ubuntu is free and open source!) If you use Linux/Ubuntu, for example, you have a real terminal application… But honestly, I find Linux to be a good operating system than Windows, in general. (However, this is just my personal opinion.) You will still need Windows though because some programs are not compatible with Linux (for example, most data visualization tools). Whether.)
Note: Which version of Ubuntu do I recommend? Well, this is again a matter of taste, so don’t take this too seriously. Maybe. As a general rule: I don’t like using the latest Ubuntu versions that are always up to date (for compatibility reasons) and somehow even years always seem to be better (18.04, 20.04, 22.04…) compared to odd versions.
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Anyway, the point is: use a Mac – or a Windows computer with Windows 10 and Ubuntu on it.
And I strongly advise against using more “exotic” operating systems for data science… for example, a ChromeBook (with ChromeOS) is a very poor choice due to its lack of compatibility with many the above software that you want to run on your computer. Similarly, I do not recommend using an iPad or any other desktop device for data science.
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I have used all kinds of Apple laptops over the past 8 years for my data science projects: MacBook Air, 13-inch MacBook Pro, 15-inch MacBook Pro… and I love them all. I have never had any problems with any of them. The cheaper, lighter, and less powerful MacBook Air has comparable performance to the more expensive and more powerful 15-inch MacBook Pro.
Well, I have to admit that the 2016-2020 MacBook versions have shown a bit of a decline in quality. Their notoriously terrible keyboard and lack of ports are a huge pain for all Apple users… Me included. But even these computers, in every other aspect (quality, usability, computing power, etc.) were still among the best on the market at the time.
Fortunately, the price drop is over and with the new 2021 14-inch Macbook Pro all the problems are fixed and we have a powerful, user-friendly and very, Very reliable to work.
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One more thing: the biggest downside to Macs is price… the new 14-inch model starts at ~$1,999.
Note 1: Important! If for some reason you decide to buy a 2016-2020 MacBook Pro, I recommend buying one *without* the touch bar. Apple – for some reason – decided to replace the usual function keys with a touch bar in the upper row of the keyboard. It’s very frustrating.
Note 2: It’s also important to note that MacBook 2016-2020 only offers USB C ports… So you’ll need to buy some adapters as well. It’s a bit uncomfortable but for now it’s like this. I always carry these three cables with me: a USB-C to USB adapter; USB-C to HDMI adapter and USB-C to Apple Lightning adapter.
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My backup computer is a Dell laptop that I bought 10 years ago (!) and it still works fine. However, it is not the same as the model I introduce here.
But my point is: Dell is a very good brand that I trust a lot. They make high-quality, long-lasting computers. In my experience, their customer service is also excellent. I have some data professional friends who use the Dell XPS model… And they support it too: The Dell XPS laptop is well suited to the needs of a data scientist.
For example. The 13-inch DELL XPS with 8GB memory and Core i5 processor seems to be a great alternative to the 13-inch MacBook Pro.
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As I described above, I prefer the 13-inch screen size. But there is also a 15-inch version here. You can also customize your XPS in many ways: more RAM, better processor,
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