Top Laptops &#038; Workstations For Data Scientists Released In 2021
The Data Science domain deals with machine learning, data analytics, data science, and statistics. This also includes linear algebra, probability, and distribution. At times, creating and running models and algorithms requires tremendous computational power, either due to the complexity or the size of the dataset being processed. As a result, companies are now creating better and more powerful devices that can run codes more smoothly and speed up your workflow to aid such problems. This article will look at some of the best laptops and workstations released recently that are ideal for data scientists to work with. Asus Rog Strix Scar III Asus is one of the most promising brands in manufacturing heavy-duty laptops. Most professionals in coding & software development or graphics designing prefer a laptop that runs every graphics-intensive task smoothly. The Asus Rog Strix Scar III is specially equipped with a powerful processor CPU to deal with such requirements. The laptop comes with an NVIDIA RTX GeForce 2070 processor GPU with 8GB DDR6 dedicated RAM. Its 1215 MHz speed enables fetching heavy applications or launching them on the system. It also comes with a 1440 MHz boost provided with 115 W.  The 9th generation Intel Core i7 9750 H processor CPU installed comes with 240 Hz. For displaying the loading app pages with high graphics resolution, the laptop’s 15.6 inches screen has a 1920*1080 IPS display. The only con of the system is that there is no ThunderBolt USB port. Image Source: ASUS Razer Blade Pro 17 Razer Blade is one of the leading manufacturers of high spec laptops all over the world. The Pro 17 model from Razer Blade comes with zero compromises and a powerhouse CPU processor for gaming. But, it is also suitable for data science-based app development. The high-performance vapour chamber cooling mechanism provided is quite reliable for complex processing. Its 1*25 Gbit Ethernet port supports 802.11 axes wireless connectivity. The NVIDIA chipset brand graphics processor GPU comes with an RTX Max Q Quad-Core processor and  8GB dedicated graphics RAM reliable for creative work environments. This model also comes with 16GB dedicated DDR4 RAM with an additional 512 GB SSD slot. The same slot is the one for storing a huge chunk of setup.exe installer files in it. As a developer, you can’t simply overlook the cross-browser responsiveness of the application. For all such heavy-duty activities, Razer Blade Pro 17 is a must-buy for data scientists. Image Source: Razer HP ZBook Fury 17 G8 The HP ZBook Fury 17 G8 is one of the best workstations released in the market this year. The system comes with a futuristic Intel Xeon processor and NVIDIA RTX A5000 graphics. The colour-accurate screen is designed for high-end professional work. The ZBook delivers desktop-like performance. It offers 45-watt Intel Tiger Lake H-class processors, both Core and Xeon, with eight cores and vPro remote management support. The memory ceiling is 128GB via four slots, with ECC available for Xeon chips. It comprises a gunmetal aluminium and magnesium body construction that feels solid and unbending. Inside is an Intel AX201 wireless card supporting Wi-Fi 6 and Bluetooth 5. With all these specifications, the ZBook Fury 17 G8 makes for an ultra-powerful workstation made for those who prioritise power and smooth execution of heavy tasks. Image Source: HP ZBook Fury 17 G8 2019 Apple MacBook Pro The Apple MacBook Pro provides ample scope to develop models and algorithms in your laptop without disturbing the ongoing applications. The powerful 9th generation 6Core intel core i7 processor CPU is matchless compared to the other available laptop models in the market. The stunning 16-inch Retina display comes with True Tone technology and provides ample scope for viewing the code developed. The latest version of Apple comes with Touch Bar ID and AMD Radeon graphics processor for powering up the CPU. Finding all these aspects in a single laptop is a priceless deal. The high bandwidth 8GBM2 memory graphics can run at a 3.5X speed. The 64GB DDR4 RAM can save multiple files on your device. Such a huge storage unit can smoothly accommodate all installer files, setup.exe files, and other graphics-intensive files. Image Source: Apple Asus Zenbook 15 UX 534 FTC AS77 Asus ZenBook15 is another smart option while you’re looking for a laptop that’s quite reliable for online gaming and algorithm development. ML app development is a complex procedure. A professional needs to place the algorithms and data based on the requirement. Sometimes, a slight miscalculation in linear algebra and probability can ruin the entire application. The 14 inches wide view 4K UHD Nano Edge Bezel display effectively visualises an app post-development. The innovative screen pad has a 5.65 inches long interactive touchscreen. The trackpad is another plus point to edit the designed app if any rectification is needed. The laptop comes with ultra-responsive NVIDIA GeForce GTX 1650 Max Q discrete graphics with 4GB memory. Perfect for developing, launching and testing heavy data applications, the Asus ZenBook15 is one for the heavy lifting. Image Source: Asus Summing up In this article, we discussed the best laptops for data science applications. Having a sound idea of the products that you’re planning to buy and the technical specifications associated with them can help you stay at bay from being misguided by marketers. But, such futuristic hardware releases do tell us that there’s much more yet to come.
This article will look at some of the best laptops and workstations released recently that are ideal for data scientists to work with.
Companies are now creating better and more powerful devices that can run codes more smoothly and speed up your workflow.
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Victor is an aspiring Data Scientist &amp; is a Master of Science in Data Science &amp; Big Data Analytics. He is a Researcher, a Data Science Influencer and also an Ex-University Football Player. A keen learner of new developments in Data Science and Artificial Intelligence, he is committed to growing the Data Science community.