Best Laptop For Data Science [Reviews 2021] – Full Buyer’s Guide
Looking for the best laptop for data science in 2021?
Stop searching; this is the right guide for you!
In this selection, I will present you the best laptops for data scientists, the most popular job of the moment!
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If you are learning or working in data science or machine learning, you will definitely need a laptop. Indeed, to gain experience, it is important to code and the portability allows you to work in any location unlike a desktop computer. The choice of a good laptop is essential since in general applications or algorithms are very greedy in resources for your machine.
As a data scientist or future data scientist, you have to manage a lot of data, collect it, process it, analyze it and interpret it. Statistical analysis needs a lot of computing power, whether it is a laptop or a PC.
You should therefore carefully examine the specifications of the laptop to ensure that it meets your needs and allows you to focus on your work rather than on solving problems related to the power of your laptop.
Top 11 Best Laptops For Data Science In 2021
ASUS ROG Strix SCAR III
The Asus brand is very famous for gaming computers. A large majority of data science professionals prefer a platform with multiple development options. For data scientists, having a laptop with limited capabilities can be tricky. With the Asus Rog Strix Scar III, you won’t have to worry about these issues.
This computer is equipped with a powerful 9th generation Intel Core i7 processor running at 240Hz which allows you to perform all graphically intensive tasks and complex calculations without any problems. It also has 16GB of DDR4 ram at 2666MHz.
If you are a data scientist passionate about video games, then I strongly advise you to buy this laptop. Indeed, the NVIDIA RTX GeForce 2070 processor is equipped with a dedicated 8 GB DDR6 RAM memory.
The 15.6-inch screen comes with a 1920*1080 IPS display. This makes it possible to display web pages or play video games with high graphic resolution.
The computer is delivered with Windows 10 home, you will not need to invest in an operating system.
PROS
CONS
- 9th generation intel core i7
- 1TB SSD with 16GB DDR4 memory.
- 8GB DDR6 VRAM memory
- No USB ThunderBolt port.
Lenovo ThinkPad P15s
The Lenovo ThinkPad P15s is equipped with an Intel Quad Core i7-10510U processor, a very good processor on the market today. It also has its own dedicated NVIDIA Quadro P520 graphics card with 2GB of ram.
It is a 15.6″ Full HD anti-glare display with a resolution of 1920×1080 pixels. It is designed with a 16GB DDR4 Ram and a 512GB SSD.
It has a bluetooth connection (if you want to connect a keyboard or a wireless mouse for example). To unlock it, you can use your fingerprint because it has a fingerprint reader.
It comes with a Windows 10 Pro so no need to invest in an operating system.
PROS
CONS
- anti-glare screen
- Bluetooth Communication
- 16GB DDR4 RAM
- Expensive
Newest HP Envy 17t
In the professional market, HP is a very recognized brand for application development. One of its flagship models is the 17T, which is very popular among data scientists and data analysts.
Its 10th generation Intel iCore 7 processor (one of the most recent generations) operates at a frequency of 1.3 GHz. This laptop comes with 16GB of dedicated DDR4 RAM which allows you to run multiple applications at once without any latency. It also has two hard drives, one 1TB HDD and a second 256GB SSD to run certain problems faster if you wish.
The USB 3.2 Type C port allows you to connect most new devices and transfer data to the computer faster. The HDMI 2.0 cable comes with a headphone/microphone combo and a multi-format SD support option.
This model is delivered with the Window 10 Pro version, no need to buy an additional operating system.
PROS
CONS
- 10th generation iCore7 processor CPU.
- NVIDIA GeForce MX330 with 4GB graphics RAM.
- Multi-format SD media card reader.
- Bluetooth headphone/microphone combo
- 3 Years McAfee Internet Key
- No such.
Lenovo IdeaPad 3
For students who can’t necessarily afford a high-end laptop, I would advise you to choose the Lenovo IdeaPad 3.
During your classes and learning, you will mainly work on sample data to test the different algorithms (hello iris.txt and titanic.txt). You won’t need a lot of computing power for your laptop.
The most important thing for you is portability and battery life. You can work in a lecture hall, a coffee shop, a library or at home in your student residence.
The AMD Ryzen 3 3250U processor has a good computing power and it will be possible to use a great majority of data analysis software and libraries. Its battery can last about ten hours without any problem, a very good point for a good mid-range PC.
The resolution is not Full HD, so if you like to work with several applications at the same time this could be a problem (one for the documentation, another for your IDE for example).
This laptop does not have a dedicated GPU, so you will be limited to using the number of threads given by the CPU, which is 4.
This model is equipped with a Windows 10 S-Mode running only Microsoft Store applications. If you want to install an application that is not available in the Microsoft Store, you will have to leave S mode.
PROS
CONS
- Very light weight
- Battery life
- 256GB SSD
- Not full hd screen
- No dedicated GPU
Apple MacBook Air Laptop
The new versions of Macbooks released in 2020/2021 are increasingly being considered by data scientists and data analysts thanks to the M1 chips. The technical environment is UNIX type, it is the most efficient environment to do data science since in general the python language works better on UNIX and some software packages, languages, libraries are not available on Windows.
Its processor has nothing to envy to Intel or AMD mobile processors, in terms of power it is even faster than the latest 10th generation Core i7 processor. It is equipped with 8 cores and boosts its performance by 3.5 times compared to previous generations. It is also optimized for machine learning.
Its portability and battery life are at the top, the Apple brand is well known for these points.
Currently, the MacBook Air is still limited to 8GB or 16GB of RAM but this is more than enough for 90% of data scientists who want to process or analyze their data on this laptop.
PROS
CONS
- Unix environment
- Battery life
- 256GB SSD
- For people familiar with mac
- GPU does not support CUDA-based applications
- 16GB of ram maximum
Lenovo ThinkPad T490
Lenovo’s ThinkPads are another laptop that can handle a Unix-like environment seamlessly, with all the powerful features needed to run large data sets. For users who want to substitute for Windows, this laptop is a great choice.
It is equipped with an Intel Quad Core i7-8665U processor which is a very good processor for performing a large amount of computation, ideal when working with large amounts of data. It has 16GB of ram and a 512GB SSD hard drive.
Note that the ThinkPads do not have a dedicated GPU (only an Intel UHD) so you won’t be able to take advantage of parallel computing for deep learning, machine learning and neural networks. But this is not necessarily a problem for people who work on different clouds (like AWS or Google cloud platform).
It is a 14-inch laptop with a resolution of 2560×1440 pixels. It comes with a Windows 10 Pro version.
PROS
CONS
- 14” WQHD
- Battery life
- 512GB SSD
- No dedicated GPU
Razer Blade Pro 17
Razer Blade is a very famous brand of computers among gamers. The Razer Blade Pro 17 model is equipped with an Intel Core i7-10875H 8-Core processor, this offers very high computing power. It is designed for resource-intensive video games, but it is also perfectly suited for analyzing very large volumes of data and running demanding applications.
For the very greedy tasks, the unibody in CNC aluminum provided is powerful and will allow to realize intensive graphic tasks in the long term.
This laptop has an NVIDIA GeForce RTX 2080 Super Max-Q graphics card with 8GB of graphics RAM which can be very helpful when running heavy tasks in parallel. The model comes with 16GB of dedicated DDR4 RAM and also a 512GB SSD hard drive (there is a version with a 1TB SSD hard drive for people who want to store a lot of data in their computer).
It has a custom vapor chamber cooling system: two custom heat exchangers and fans to maximize heat dissipation and airflow.
It features a 17.3″ FHD display clocked at 300Hz and 3840 x 2160 (4K) resolution. It comes with a version of Windows 10 so no need to invest in an operating system.
If you need a laptop where you can perform all these tasks smoothly, I really recommend the Razer Blade PRO 17.
PROS
CONS
- 8 GB of dedicated RAM for graphics intensive tasks.
- A very powerful processor
- 512GB SSD
- No particular default
Dell G5 15 Gaming Laptop
This DELL laptop is equipped with an AMD Ryzen 7 4800H processor, it is a very powerful processor to perform heavy calculations. For data scientists who work on very large volumes of data, this is not negligible.
It has 8GB DDR4 RAM and a 512GB SSD hard drive. Its graphics card is an AMD Radeon RX 5600M.
Its screen is Full HD with a resolution of 1920×1080 pixels clocked at 144hz, it also offers an anti-reflection technology that reduces eye fatigue and increases the field of vision.
It has a Bluetooth connection, which allows you to connect a microphone or a headset without having lots of wires lying around.
PROS
CONS
- A very powerful processor
- 512GB SSD
- Anti-reflection technology
- Only 8 GB RAM
ASUS ZenBook 15 Ultra-Slim Laptop
The ASUS ZenBook 15 Ultra-Slim is one of the best laptops for data science. With its 10th generation Intel Core i7-10510U Quad Core Processor you will have no problems running heavy programs. It also has a dedicated NVIDIA GeForce GTX 1650 graphics card.
Its 15.6-inch 4K UHD widescreen display with 4-way NanoEdge bezel has a screen-to-body ratio of 92%; one of the highest on the market. Rarely offered among other laptops, the ASUS Zenbook 15 features an innovative screenPad: A 5.65-inch interactive touchpad for smarter control and multitasking.
For users who are adept at voice recognition, this laptop works with Amazon Alexa Voice Service that helps you with tasks or entertainment for example. For better security, it also has a built-in infrared camera for facial recognition with Windows Hello.
This computer has 16GB RAM and a 512GB SSD hard drive
The Asus has an HDMI cable connectivity option with a USB Type C charger.
Wi-Fi 6 support is provided with 802.11 ax Wi-Fi support. The Bluetooth 5.0 port comes with an SD card reader.
It is sold with a version of Windows 10.
PROS
CONS
- A very powerful processor
- 16GB DDR4 RAM + 512GB SSD.
- Innovative ScreenPad
- Battery life (~6hours)
Apple MacBook Pro
The Apple MacBook Pro comes with the new M1 chip that delivers performance never before seen in a MacBook. For machine learning, it’s a great processor. Its 8-core processor offers performance up to 2.8 times faster than previous generations.
For applications and games that require graphics, this Macbook offers a GPU with 8 cores. Its 16-core Neural Engine technology boosts the Macbook Pro’s machine learning performance to a level rarely seen in a laptop. Automating video analysis, speech recognition, and image processing will be a breeze.
Its beautiful 13-inch Retina display with True Tone technology gives you plenty of room to view your data.
The ultra-fast SSD storage unit (512GB at least) provided in this laptop is efficient in helping you store all your files. The RAM memory is 8GB.
Its autonomy can go up to 20 hours, very exceptional in the current laptops. For more security, this Macbook Pro is equipped with Touch ID technology that allows you to unlock your laptop with your fingerprint.
PROS
CONS
- New M1 hip
- 16-core Neural Engine
- Touch ID and Touch Bar
- Battery life (~20 hours)
- No particular default
Dell XPS 13 9360
The Dell XPS 13 is equipped with an 8th generation Intel Core i7-8550U processor.
It has 8GB of DDR3 ram with a 256GB SSD hard drive which is the minimum recommended for a laptop for data science.
Its screen is 13.3″ with a Full HD resolution of 1920×1080 pixels. It is an anti-glare display for better visibility.
It is sold with a Windows 10 Home operating system.
PROS
CONS
- Battery life
- DDR3 Ram
Best Laptop For Data Science: What To Consider
If you currently own an ordinary laptop, it may not be that effective at handling basic tasks for a data scientist or data analyst.
Therefore, it is important to make sure that the laptop you wish to acquire is equipped with the primary features to analyze or process your data.
We will therefore see what are the most important factors to take into account when making your purchase.
Best Laptop For Data Science : Processor (CPU)
It is important to always buy the latest generation of processors. Currently Intel processors are at the 11th generation and AMD processors at the 5th generation. Processing power, new hardware compatibility or thermal management have increased considerably since the last generation.
A second aspect to take into account is the number of cores and threads. Indeed, in machine learning it is often necessary to perform parallel calculations such as the Random Forest which allows you to set the number of cores to use for training. By definition, cores are the number of independent processors in a processor. Threads are instructions that can be processed by a single core. I would advise you to take a processor with 4 cores and 8 threads minimum.
The frequency of the processor (noted in gigahertz) is also very important if you want to have a fast processor.
A last element to take into account is the cache memory. The cache serves as a buffer between the RAM and the processor. It allows to keep the data or instructions often used so that they are directly available for the processor. The minimum recommended is a cache memory of 8MB.
Here is a list of the best CPUs of the moment:
| CPU | Cores | Threads | Base clock |
|---|---|---|---|
| AMD RYZEN 9 5950X | 16 | 32 | 3.4GHz |
| AMD RYZEN 9 5900X | 12 | 24 | 3.7GHz |
| AMD RYZEN 9 3950X | 16 | 32 | 3.5GHz |
| AMD RYZEN 7 3700X | 8 | 16 | 3.6GHz |
| AMD RYZEN 5 3600 | 6 | 12 | 3.6GHz |
| Intel Core i9 10900KF | 10 | 20 | 3.7GHz |
| Intel Core i9-9900K | 8 | 16 | 3.6GHz |
| Intel Core i5 10600KF | 6 | 12 | 4.1GHz |
| Intel Core i5-10400F | 6 | 12 | 2.9GHz |
| Intel Core i7 10210U | 4 | 8 | 1,8 GHz |
Best Laptop For Data Science : RAM
Many people consider RAM to be the most important criterion, but you should know that increasing the size of RAM does not speed up your computer. A RAM with a larger capacity will allow you to perform several tasks at once. The recommended minimum is 8GB because the operating system takes up about 3GB of RAM for proper execution. If you can afford to upgrade to 16GB, I recommend it. This will give you the possibility to install virtual operating systems or to perform more complex tasks in data analysis.
The speed of the RAM bus should also be taken into consideration. DDR4 RAMS support a bus speed of 3200 MHz and the higher this value the faster your computer will be.
Best Laptop For Data Science : Storage
This is a very important criterion. Most laptops are equipped with HDDs. These hard drives are very slow, it takes a long time to start or open a new program.
If you want to invest in a good laptop for data science I would advise you to get an SSD hard drive. If your laptop supports NVMe SSDs, invest in one. Indeed, they are 6 times faster than a regular SSD hard drive. The ideal size is 512GB. Don’t go below that.
Best Laptop For Data Science : Graphics Card (GPU)
The best-known graphics card manufacturers are NVIDIA and AMD. If you are a fan of the TensorFlow deep learning library, I recommend you to buy an NVIDIA, it uses the CUDA processor which is only available on these graphics cards.
One of the main advantages of having a dedicated graphics card is that it has an average of 100 cores unlike a standard CPU with 4 or 8 cores.
Also, prefer the GPU with at least 4GB of RAM.
Best Laptop For Data Science : Display
Most screens emit blue light that is harmful to your eyes. If you spend long hours in front of your screen, choose a screen with blue light filtering and flicker-free technology.
A 15.6″ or 17.3″ screen is recommended. Do not go below this size, especially if you are working on several programs at the same time. You may want to consider using a second monitor to connect to your laptop.
Frequently Asked Questions
What type of laptop do I need for data science?
If you are a data scientist, the best laptop you should buy is one that you can easily connect to the cloud environment. If you need to process data quickly, it would be best if you have a laptop with good high-end specifications.
I recommend a minimum configuration of 256GB SSD and at least 16GB RAM, with a 9th generation quad-core i7 processor or higher.
How much RAM do I need for data science?
The minimum recommended is 8GB but if you are using neural networks and other machine learning or deep learning algorithms opt for 16GB.
What is meant by data science?
Data science is a multidisciplinary approach to data exploitation. It involves many fields of expertise. For example, applied mathematics, statistical sciences, computer science, data engineering, artificial intelligence and the concept of machine learning. It uses different tools related to information technologies:
- Data visualization
- Machine learning
- Data warehousing
- Probability models
- Software and utility programming
Conclusion
In this review, we have selected the best laptops for data science. It’s up to you to see which one to choose to meet your needs. Factors to consider when making your purchase are processing power, RAM and hard drive size.
If you have any suggestions on a data science laptop that I haven’t mentioned in this article, let us know in the comments or via our contact page.
See you soon for more reviews!
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