If you want a laptop rather than a desktop for working on machine learning, it is likely that the primary reason is portability. However, portability alone won’t suffice for helping you be your best productive-self. It’s also important to factor in other crucial laptop performance elements such as high processing power, GPU, RAM, and battery life.
From arranging datasets to creating predictive models – regardless of the types of machine learning work you do, you’ll not find yourself short of configuration options. What you need to focus on is finding the right balance in specifications so that you have all the necessary hardware setup to back you through and through. To save you from the hassle of going through the endless options available online, we’ve hand-picked some of the best laptops for machine learning.
The laptops we’ve compiled below have similarities and differences in technical specifications and price. Whether you are looking for a budget-friendly laptop or one with the most powerful performance, we’re sure that you’ll find the right fit in the list.
Minimum requirements for the best laptops for machine learning of 2020
But before you begin, go through this brief overview of the must-have specifications to narrow down your choice and make your laptop hunting journey easy:
- CPU – Your productivity takes a hit if the laptop you’re using doesn’t have a good processing power. Laptops with Intel Core i7 processor and above have a powerful and faster performance that’s suitable for machine learning.
- RAM – 16 GB of RAM is the minimum recommendation for working on various types of machine learning tasks and subsets. Higher RAM speeds computation time, that’s needed for heavy machine learning algorithms such as random forest and neural networks.
- GPU – Desktop-class GPU is what you want to look for. Some of the latest-generation graphics, such as the GeForce GTX 1070 and AMD Radeon Pro 5500M can handle even the most complex machine learning tasks.
- Storage – Considering the fact that datasets continue increasing, choosing a laptop with a minimum of 1 TB of storage is a must. For SSD, a minimum of 256 GB of storage is recommended.
- Battery life – Battery life often gets overlooked when it comes to choosing a laptop for technical work requirements. A laptop that supports 5 to 6 hours of continuous usage helps you get the most out of the portability factor.
List of Best Laptops for Machine Learning
- Lambda TensorBook – Best overall
- Eluktronics Pro-X 17.3 inch – Best performance
- MacBook Pro 16 inch – perfect for work and modern
- Razer Blade 15 2019 – best sleek design
- Gigabyte AERO 15 SA-7US2130SH – backed by Microsoft Azure machine learning
- Lenovo ThinkPad X1 Extreme Gen 2 – supports upto 4 monitors
- Acer Predator Triton 700 – Unique keyboard and good sound quality
- HP Spectre x360 – best touchscreen for machine learning
- Asus ROG Zephyrus S 2019 – gaming beast with 3 fan modes
- Dell G7 17 – hardcore performance
- HP Omen 15 – high end
Review of Best Laptops for Machine Learning
Lambda TensorBook – Best overall
Whether you are a student or a working professional, things get easier for you if the laptop you choose is specifically designed for the type of learning/work you do. Just like the way premium touchscreen 2-in-1 laptops are best suited for creative professionals, the Lambda TensorBook is an unmistakable choice for machine learning students and professionals.
Lambda TensorBook sets itself apart from the rest as it comes included with several machine learning/deep learning frameworks such as Keras, TensorFlow, and PyTorch. Apart from the pre-included software libraries, Lambda TensorBook also deserves the moniker of one of the best laptops for machine learning with its powerful performance.
made for machine learning
A 10th generation Intel i7 8 core CPU powers this laptop with 2.3 GHz of base frequency and 5.1 GHz of peak computing performance.
Its NVIDIA GeForce RTX 2080 Super Max Q GPU backs you up with all the graphics processing power you need for using open-source deep learning platforms that encompass a wide range of libraries and tools. The whopping 64 GB DDR4 RAM of this laptop perfectly complements the GPU’s performance and helps you steer clear from performance slowdowns. Also, the fast read and write speeds of the laptop’s 2 TB SSD storage works to your productivity advantage.
This model has a 15.6 inch full HD display. The stunning 144 Hz refresh rate of the display helps you get all the visual cues you need to use your machine learning application productively. Also, the cooling system of this laptop is on point. Ports that are available in this model include three USB 3 Type A ports (one supports power charging), one Thunderbolt 3 port, one microSD card reader, one ethernet port, one HDMI port, one headphone jack, and one mic jack.
Pros:
- CPU and GPU well-suited for machine learning
- Lambda Stack comes pre-included
- Good wireless connectivity performance
Cons:
- Overall chassis is a bit bulky
- Can run a bit loud during heavy usage
Eluktronics Pro-X 17.3 inch – Best performance
If there’s one powerful laptop that you can blindly choose for machine learning, it’s Eluktronics Pro.
This laptop sports an ultra-high hardware configuration that’s in a league of its own. Intel core i7-6700K quad core that clocks 4.0-4.2GHz with turbo boost offers beastly power needed for handling even the heaviest workload. 6 GB GDDR5 VRAM NVIDIA GeForce GTX 970M graphics of this laptop helps the processor deliver more power for intensive computing.
the undisputed machine learning workstation
Things get more interesting with the in-built GPU overclock software that helps you get the most out of the laptop’s graphics processing power. Overall, it’s safe to say that Eluktronics Pro employs one of the best GPUs for deep learning, neural networks, and predictive models.
Eluktronics Pro has the best-in-class DDR4 RAM of 64 GB for the range-topping model. The RAM helps make sure that the datasets you’re working on stay in memory. When working on multiple data sets and prototype models, viewing them under a single console becomes easy. Enter the whopping 17.3 inch full HD display of this laptop that offers stunning viewing angles. The large FHD display makes Eluktronics Pro no less than a desktop replacement as it eliminates the need to use external displays.
The laptop’s battery life can last up to 5 hours during intense usage. If you are remotely working on machine learning, the better-than-average battery life won’t let you down. Also, Eluktronics Pro strikes a fine balance in the storage department with 1TB hard disk capacity and 128 GB SSD storage.
Pros:
- Desktop-class performance
- G-Sync availability
- High graphics processing power
Cons:
- A bit bulkier and larger
MacBook Pro 16 inch – perfect for work and modern
There is no perfect or ultimate laptop for working on machine learning. However, the new MacBook Pro comes close. This new variant is improved in all the areas where its predecessor lagged behind, including heating problem, CPU management, and keyboard. With an additional server and cloud support to back you up, the MacBook Pro can handle different types of machine learning tasks you throw at it.
a nearly-perfect machine learning laptop
The 2.3GHz 8-core Intel Core i9 processor that supports turbo boost up to 4.8GHz is highly suitable for vectorization processes, making the MacBook Pro one of the best laptops for deep learning. The 16 GB RAM coupled with AMD Radeon Pro 5500M graphics creates a suitable hardware architecture for seamless parallel computing that’s needed for machine learning algorithms to process large data sets.
Comfort is often overlooked when hunting for the best specifications. Unlike many high-end laptops, the MacBook Pro is designed to be highly comfortable to use. The sleek and comparatively lightweight body design of the laptop bears testimony to this. Coding machine learning models become a breeze with the 16inch Retina display that offers an immersive and comfortable viewing experience.
It’s a known fact that MacBooks have one of the best trackpads. The Force Touch trackpad and the Touch Bar help you get your work done in the most interactive and easy ways possible. Need to keep all the coding and training ensembles with you? The 1TB SSD storage capacity of the new MacBook Pro provides the perfect solution.
Pros:
- Best-in-class processing power and thermal management
- Reliable and easy usability
- Excellent battery life
Cons:
- Limitation in ports
Razer Blade 15 2019 – Sleek design
High-end gaming laptops do well in the machine learning territory, and the Razer Blade 15 2019 is a perfect example of this. The powerful internal configuration of the Razer Blade 15 2019, primarily designed for gaming, provides you with the right platform to efficiently work on machine learning, making it one of the best laptops for machine learning.
beefed-up specs to meet your machine learning requirements
The value that you get in this laptop’s price point starts with its powerful 4.5 GHz Intel core i7 processor. The processor is paired with NVIDIA GTX 1660 Ti graphics core processor and 16 GB DDR4 RAM to deliver an incredibly powerful performance that can take on machine learning. Standard usage such as browsing and multimedia are a cakewalk for this well-thought out, powerful configuration. Also, the laptop packs a punch with 1TB HDD and 256 GB SSD storage capacity combo.
Apart from uncompromising performance, the Razer Blade 15 2019 prioritises usability and personalization as well. Bringing ease of use to the table is the laptop’s full HD 15.6 inch display with thin bezels that supports 100% sRGB color.
The Razer Blade 15 2019 gives a new definition to workstation mobility with its sleek and compact CNC aluminum unibody design. When it comes to connectivity, the Razer Blade 15 2019 gives a strong competition to desktop rigs with its combination of 3 USB 3.1 ports, 1 Thunderbolt 3 port, 1 HDMI port, and 1 mini display port.
Pros:
- Powerful performance
- Good battery life
- Good mobility
Cons:
- Not the best keyboard
Gigabyte AERO 15 SA-7US2130SH – backed by Microsoft Azure machine learning
Gigabyte AERO 15 SA-7US2130SH embodies the utilitarian benefits that artificial intelligence and machine learning bring. The laptop is backed by Microsoft Azure machine learning which analyzes user data on the cloud and optimizes battery life and performance. If you are working on GPU-intensive machine learning, the Azure machine learning support will automatically and intelligently optimize CPU and GPU wattage. In other words, this laptop can adapt to your machine learning work requirement at any given moment and help you give your best shot, every time.
an embodiment of machine learning’s practicality
The range-topping model of the Gigabyte AERO 15 SA series gets its horsepower from a 6-core 9th Gen Intel Core i9-9750H processor. The laptop’s powerful processor works in conjunction with the NVIDIA GeForce GTX 1660 Ti GDDR6 6GB graphics that supports NVIDIA Optimus technology. Backing up the ultra-powerful computing of this laptop is the 16GB DDR4 2666MHz Samsung DRAM module.
Getting your machine learning work done gets more convenient with the 15.6 inch full HD display that has ultra-thin bezels. If you need to store all your work essentials, simply put the 512GB SSD storage capacity of the laptop into use. Gigabyte AERO 15 SA-7US2130SH rocks in the keyboard department as well.
The comfortable-to-use and programmable keyboard is just what you need to code and create prototype models. Similar to the new MacBook Pro, Gigabyte AERO 15 SA-7US2130SH leads the pack with one of the best thermal management. Apart from better heat management, the sleek and durable body design also makes this machine ‘lappable.’
Pros:
- Top-of-the-line performance management
- Great connectivity options
- Premium look and feel
Cons:
- Weight is a bit of the heavier side
Lenovo ThinkPad X1 Extreme Gen 2 – supports upto 4 monitors
The ThinkPad series from Lenovo has been one of the go-to choices for working professionals and content creators over the years. The ThinkPad X1 Extreme Gen 2 steps up in the performance game and has been designed to meet intensive technical work requirements, making it one of the best laptops for big data, machine learning, programming, AI systems, and business analytics.
uncompromised power to you
If you are someone who works on machine learning on a regular basis, you can’t go wrong with this powerful machine. The core computational power of Lenovo ThinkPad X1 Extreme Gen 2 lies in its beefed-up 9th Generation Intel Core i7-9750H processor that clocks up to 4.50GHz with turbo boost. Adding more computational power is the NVIDIA GeForce GTX 1650 graphics of this laptop that helps you maintain efficiency and productivity when doing various types of GPU-accelerated machine learning.
You also get to access the power of 16 GB DDR4 RAM for all your complex machine learning computation needs. Talking about complex computation, this laptop supports up to four independent monitors. This feature is highly useful when training and iterating various machine learning algorithms. But that’s not where the practicality of the ThinkPad X1 Extreme Gen 2 ends.
The laptop also includes the Glance technology which offers gaze tracking. With just a move of your eyes, windows shift and the cursor automatically focus through gaze tracking. Comfortable viewing isn’t a problem at all as it’s 15.6 inch full HD display gets the job done. SSD storage capacity on this laptop is standard at 512 GB.
Pros:
- Powerful performance
- Utilitarian features
- Classic Thinkpad keyboard improves usability
Cons:
- Battery life takes a hit
Acer Predator Triton 700 – Unique keyboard and good sound quality
Acer Predator Triton 700 is built for gamers but can be machine learning techies’ best companion. After all, it packs a powerful hardware configuration that’s assembled to let you access latest-generation computing.
The impressive hardware setup of this laptop starts with a 7th gen Intel core i7-7700HQ processor that’s consistently cooled by 2 aeroblade 3D fans and 5 copper heat pipes. An overclockable NVIDIA GeForce GTX 1080 GPU works wonders in complementing the overall performance of the processor. And not to forget about the impressive 32GB DDR4 RAM that works in sync with the laptop’s CPU and GPU.
overclocking performance in a sleek footprint
Acer Predator Triton 700 has a unique keyboard and trackpad configuration. Instead of the usual setup, this laptop features the trackpad on the top area and keyboard at the bottom. The keys are responsive and have a good travel that offers a mechanical feel. If the 15.6 inch full HD display isn’t enough for you when getting multiple tasks done, you have the option of connecting multiple external displays to this laptop.
If you are somebody who prefers listening to music while working, you are in for a treat. The 3D Dolby Atmos sound unit of this laptop delivers immersive audio experience. Plug in your headphones and let the stunning sound quality inspire more productivity in you. The 512GB SSD storage has fast read and write capabilities.
Pros:
- Impressive RAM
- Compact body design
Cons:
- Can run hot at times
HP Spectre x360 – best touchscreen for 2 in 1
HP Spectre x360 packs all the features essential to getting any type of machine learning work done without any performance issues. A consistently powerful performance is one of the biggest highlights of this laptop, thanks to the 4.6 GHz Intel Core i7 processor it houses. Arranging datasets, training machine learning algorithms, modelling input data and creating predictive models – you name it, the high clock speed of the processor won’t let you down when it comes to working on different types of machine learning tasks.
A perfect all-rounder
Equally powerful and impressive is the RAM of HP Spectre x360. The 16 GB DDR4 RAM of this laptop will help you make sure that multiple machine learning processes stay in memory and do not get refreshed.
The CPU and RAM configuration of this laptop gets an extra performance boost from the powerful NVIDIA GeForce MX150 graphics. With the top-of-the-line graphics, you can steer clear from the hassle of lags when working on large data sets and training complex machine learning algorithms. Combining the power of the laptop’s internal specification with an additional GPU library and/or cloud support will help you get the best of its performance.
Another standout feature of HP Spectre x360 is the tablet mode. The 360° hinge rotation of the display helps you convert this powerful machine into a handy tablet. If you are a college student studying machine learning or a working professional attending machine learning course, you can convert the laptop into tablet mode and use the dedicated stylus to make note-taking simpler and fun.
Using this laptop gets easier with the combination of Windows 10 Home, multi-gesture trackpad, and a stunning 15.6 inches AMOLED touchscreen display with thin bezels.
Battery life isn’t the best selling point of this model as it may last only up to 4 hours of high-intensity usage. But it sure does provide over 10 hours of runtime for standard use. Lastly, the 512 GB SSD storage capacity of HP Spectre x360 makes no mistake in helping you store everything you need.
Pros:
- Reliable all-rounder performance
- Stylish design
- Computer and tablet mode
- Impressive viewing
Cons:
- Slight heating
- Not the best battery life
Asus ROG Zephyrus S 2019 – gaming beast with 3 fan modes
Versatility and power – these are the two core elements that define some of the best computers for machine learning, programming, and high-end gaming. Asus ROG Zephyrus S 2019 combines both of these elements to create an incredibly-powerful mobile workstation platform. Every hardware component of this laptop ooze unrivaled performance.
versatility in power
The 9th Gen Intel core i7-9750h hexa core processor makes Asus ROG Zephyrus S 2019 an absolute powerhouse. Like the Gigabyte AERO 15 SA-7US2130SH laptop, this machine stands out with in-built performance optimization. But unlike with the former, performance optimization is done by the 3 fans modes in the Asus ROG Zephyrus S 2019.
The fans switch to turbo mode during intense usage to make sure performance isn’t compromised. Completing the core hardware ensemble of this laptop is 16 GB DDR4 RAM and Nvidia GeForce RTX 2070 graphics. The graphics card is scalable and can be overclocked till 1700+ MHz.
Asus ROG Zephyrus S 2019 takes the path of the Razer Blade 15 2019 laptop in terms of body design and build quality. The sleek and robust chassis of this laptop helps you get the most out of portability and mobility.
Display is great as well; a 15.6 inches full HD display with thin bezels matches the hardware architecture of this laptop. And out of what you’d least expect, this laptop does well in the storage department. It has a whopping 1TB SSD storage where you can store and have quick access to all your machine learning graphs.
Pros:
- Good thermal management
- Performance reliability at its best
- Sleek and compact footprint
Cons:
- Fans get a bit noisy during turbo boost
- Not the best audio speakers
Dell G7 17 – hardcore performance
When was the last time you saw a high-performance laptop sport an aesthetically-pleasing and elegant design? Dell sure knows how to give its laptops balanced aesthetics that blend well in different types of working environments such as corporates, boot camps, and at-home freelancing gigs. But looks aren’t what the Dell G7 17 is all about. The laptop makes a stand for itself in the highly-competitive market with its powerful performance.
an unmistakable combination of performance and aesthetics
The right mix of latest-generation hardware of this laptop can handle machine learning duties. On paper, the Dell G7 17 gets its unrivaled processing speed from the 9th gen Intel core i7-9750H processor.
NVIDIA GTX 1660 Ti 6G GDDR5 GPU adds more computing juice to help you get the most done. With 16GB DDR4 RAM, this laptop gets a standard rating in the memory department. Another important value that the Dell G7 17 brings is faster load time for which the credit goes to its 512 GB SSD storage.
Dell G7 17 also leads the pack with its large display size which measures at 17.6 inch. The gaming-grade viewing of the display adds more convenience to your regular work schedule. Processing-intensive machine learning-related tasks are handled well, thanks to the laptop’s dual-fan cooling system.
Dell G7 17 tops in another area where many competitors lag behind, and that is keyboard. The comfortable layout and smooth travel of the backlit keyboard makes coding convenient.
Pros:
- Performance outweighs price
- Sophisticated aesthetics
Cons:
- Noisy at times, during intense usages
- Non-bezel-less display design
HP Omen 15 – High end
Do your machine learning work without breaking a sweat with HP Omen 15. HP didn’t go wrong in housing a powerful hardware configuration in a stylish and durable chassis to create a mobile workstation for creators, gamers, and techies. Consistency in performance is critical to getting all your technical work done in time, and this laptop is all about that.
makes no compromise in performance
HP Omen 15 draws its power from the 6-core, 9th-gen Intel core i7-9750H processor that’s paired with NVIDIA RTX 2070 (Max-Q) 8GB GDDR6 dedicated graphics. A 32BG DDR4 RAM addition makes this laptop a tough competition in the price point it’s available at. Whenever there’s a need to store machine learning datasets and graphs, the 512GB SSD storage with fast read and write capabilities is there to back you up.
When it comes to upgradeability, you get plenty of options with this laptop, thanks to its single-panel access to internals that make it a desktop-like computer for machine learning.
The 15.6 inch 4K ultra HD thin bezels display of HP Omen 15 does a good job with lag-free on-screen visuals. Lastly, the overall body design of this laptop doesn’t go unnoticed. The ultra-modern aesthetics of this laptop makes it worth showing off.
Pros:
- Great display
- Reliable performance
Cons:
- Weight is a bit heavy
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Conclusion
There’s no ultimate and best laptop for machine learning as the hardware requirements you have completely depends on the type of machine learning you work on. However, the high-performance laptops included in this list sure do a great job of helping you create a mobile workstation and get most (if not all) of your work done.
In order to improve the computing power of the laptop you choose for your machine learning requirement; we suggest using add-ons such as external GPU and/or a cloud-based GPU library. You can also use other open source platforms to open up room for scalability and leverage the power of your laptop.
Last update on 2020-12-26 / Affiliate links / Images from Amazon Product Advertising API