Best Laptop for Machine Learning

So, you’re after a laptop to house whatever algorithmic monstrosity you have planned but are unsure of which kind of laptop to go for. Any old laptop won’t do if you’re planning on deploying your training scripts onto the machine itself instead of hosting on rented instances online. 

Fortunately, we’ve already cracked the code when it comes to the laptop market and have found five products that will be able to run machine learning instances, some skating by the minimum requirements and others reaching the maximum. 

How did we make our decision? Below our product selection you can find a buyers’ guide and an attached FAQ where we elaborate about what to look for in a good laptop, both in general and for machine learning, so that we can be on the same page. This way you can appreciate which laptop will be the best for what you have planned and get the best one.

In a hurry?
This is our Winner!

Our Pick

Are you busy? We’ve got our top choice right here if you can’t stick around for too long. It was the MSI GS65 Stealth-432 that came out on top when all was said and done. Not only does it look great and is from a recognizable manufacturer of high-quality gaming laptops, this specific product had the exact specs you’d want in a machine learning laptop. See why we chose it in more detail below:

  • Has both an Intel Core i7-9750h CPU and NVIDIA GeForce RTX 2070 GPU to guarantee some of the highest performance and graphics currently available, which will translate into speedy calculations for your deep learning machine.

  • As much on-device storage as you can get thanks to a 1TB NVMe SSD. 32GB of RAM also helps with multitasking and can be upgraded to an ample 64GB.

  • Looks great thanks to MSI’s subtle color-trimmed design and large 15.6” anti-glare wide monitor screen.

Best Laptop For Machine Learning - Reviews

MSI GS65 Stealth-432 15.6' Gaming Laptop, 240Hz Display, Thin Bezel, Intel Core i7-9750H, NVIDIA GeForce RTX2070, 32GB, 1TB NVMe NVMe SSD, Thunderbolt 3

Our Top Pick

Our rating

It may be from a reputable gaming laptop brand, but it stands to reason that these powerhouses of portable performance are a great choice when seeking laptops up to the task of managing and executing machine learning software. That’s why our top choice is the MSI GS65 Stealth-432, it has exactly all of the specs you’d need and want in a high-performance laptop. Those specs are an Intel Core i7-9750H CPU and an NVIDIA GeForce RTX 2070 GPU. Designed to process the most life-like games with impeccable graphical fidelity, they’ll host your deep learning machine with relative ease. There’s also the RAM at 32GB, which is fine for your purposes, but can be upgraded to 64GB if you want to go all in. 

Lastly with the specs, there’s the storage which is made up of one 1TB NVMe SSD which is good for on-device storage, but you’ll probably prefer to have externals on hand too. With that techy stuff out of the way, it’s also just a great laptop all around. As mentioned, it’s tailor made for gaming and so can do that, and the screen you’d use to play is anti-glare. MSI’s unique design style is back with their distinguishable logo and colored trims along the edges of the laptop make it pleasant to look at.

It's the most expensive on this list, but with PC specs there’s little room for subjective evaluation. That is to say, a product either has the specs you need or not, and this laptop has them in spades.

Pros

  • Features an Intel Core i7-9750H CPU and NVIDIA GeForce RTX 2070 GPU to guarantee some of the highest performance currently available, all with a 1TB NVMe SSD for maximum on-device storage
  • 32GB of RAM upgradeable up to 64GB for memory expansion, if needed
  • 15.6” anti-glare wide monitor screen
  • MSI’s distinguishable logo and color trims make it a good looking laptop

Cons

  • The most expensive product on this list

The next laptop in our list is a very compact one, but don’t let its unassuming size make you underestimate its power. Within the Razer Blade 15’s small casing is a 9th Gen Intel Core`i7-9750H processor with six cores for higher multitasking functionality and an impressive NVIDIA GeForce RTX 2060 which, whilst not as powerful as the 2070 that come in this list have, is more than enough for machine learning. 

It's definitely more capable on the performance front though, and its memory and storage capabilities look underwhelming in comparison. That isn’t to say they’re bad, having a 512GB SSD and 16GB of RAM which would be considered ample in any other computer, but for the purposes of training machine learning software you’ll probably end up wanting more. Fortunately for you, the lab coats at Razer seem to have foreseen this and have futureproofed this laptop by adding upgradeability for the SSD and dual-channel memory RAM inserts. Without this upgradeability this laptop would’ve been lower down in the list, but this futureproofing means that you can add extra performance to its already impressive specs as and when you need them.

Pros

  • Six Core 9th Gen Intel i7-9750H processor with powerful RTX 2060 graphics card
  • 512GB SSD storage and 16GB of RAM, adequate enough to get started with machine learning software
  • Upgradeability means that the SSD/HDD, the RAM, and even the GPU can be upgraded in the future to guarantee continuing high-end performance. This makes up for the shortcomings in storage and memory too

Cons

  • Very expensive

Since we opened the list with some of the most expensive, but suitable, products on this list where machine learning laptops were concerned, our next product is a cheaper option. It’s the Dell Inspiron 15 7000, a relatively lower-power laptop that has a respectable 9th Generation Intel Core i7-9750h processor and NVIDIA GeForce GTX 1050 graphics card. It’s very portable and lightweight thanks to its magnesium alloy construction and has dual fans for overheating reduction. This laptop also has an added security detail by virtue of its fingerprint reader.

Offering great performance for a laptop of its price point, for the purposes of machine learning it can only be described as adequate due to limitations its lack of storage and memory have. A 256GB SSD is the bare minimum in terms of SSD storage, and the 8GB RAM is usually enough for most laptops but may struggle with intensive work such as machine learning. We’d recommend upgrading and using externals, which you should be able to get with the money you can save on this very affordable laptop.

Pros

  • Has a 9th Generation Intel Core i7-9750H processor with NVIDIA GeForce GTX 1050 for adequate performance
  • Magnesium alloy construction to be stable but rigid
  • Dual-fans and drop-hinge design stop the laptop from overheating, adding to the battery life as a result
  • Cheapest on this list

Cons

  • Bare minimum in terms of SSD space and lacking in RAM, will both need upgrading

Another high-end gaming laptop comes in at number four, the ASUS ROG Zephyrus S GX701 can come with either an NVIDIA RTX 2070 or 2080 depending on your preference since the lower graphics card will do the trick just fine. Alongside the RTX series graphics card is another 9th Gen Intel Core i7-9750H to guarantee consistent high performance. As far as specs are concerned, it also boasts a new 1TB NVMe SSD again like our top option but fell down the list somewhat due to the fact it has 16GB. It’ll still work just fine with 16GB, but we’re here to tell you the best, and what we consider the best is 32GB and up.

Having looked at the specs, it must be said that this laptop is quieter than it has any business being for how powerful it is. This is in part thanks to its ROG Active Aerodynamic cooling system which uses quietened fans that keep the device cool and near-silent which, besides not being a nuisance, prolongs the battery by conserving heat energy. Speaking of retaining battery life, it also has a GPU Switch Mode designed for gaming in which you can set your laptop to a weaker, power saving mode focused on longevity or a stronger, high-performance mode focused on going all out.

Pros

  • Have a choice between NVIDIA RTX 2070 or 2080 GPUs, but either would work alongside this laptop’s 9th Gen Intel Core i7-9750H processor to deliver sustained high performances
  • 1TB NVMe SSD, great for reading and writing data faster
  • More intelligent ROG Active Aerodynamic cooling system ensures the laptop stays cool and quiet, boosting battery life
  • GPU Switch Mode: Switch between integrated or discrete options for either power saving capability or high performance

Cons

  • 16GB should do the job well enough, but 32GB is better
  • Very expensive

The last product on the list is another high-performance gaming laptop, the Acer Predator Triton 700. It comes with a 7th Gen Intel Core i7-7700HQ processor and a GeForce GTX 1080 graphics card that’s overclockable to get every ounce of power out of this device. The 1080 is a staple high-performance card that was the best option for GPUs until NVIDIA released their RTX series, but still performs more than admirably. This product also hits the 32GB recommended threshold and has 512GB of RAM, lower than what is ideal but any setup you go for will likely have to be bolstered by externals anyway due to the sheer amount of data you’re working with. The 512GB option is a choice, a combination of two 256GB SSDs, and we’d recommend you pay out some more for that version.

It has three-cell Li-Ion batteries which only carry about two hours of charge, short even for the standards of a heavy-hitting gaming laptop. This means that it’ll need to be plugged in near-constantly if used for machine learning training, which will kill the portability of this model. Portability isn’t as important as whether it can perform machine learning, hence its inclusion in the list, but you should be aware of this limitation before buying.

Pros

  • Contains an i7-7700HQ CPU with overclockable GeForce GTX 1080 GPU for bursts of more power
  • 512GB worth of SSD storage and 32GB RAM, more than enough to run deep learning algorithms on both counts
  • 120Hz refresh rate with NVIDIA G-SYNC technology gives this laptop a great display

Cons

  • Three-cell Li-Ion batteries only carry approximately two hours, and will need plugging in a lot

Best Laptop for Machine Learning - Buyers Guide

What to look for in a laptop for machine learning

It’s important to consider which laptop can handle the job you want it to, and so you’ll generally need to make considerations for processing power and performance, storage, battery life, and portability. With those in mind let’s run through most of the spec categories and point out which features are desirable, and which are not.

Processing Power

A CPU is essentially the hub of most calculating activity done on your prospective computer choice, so make sure that it’s a CPU with as many cores as possible without breaking the bank. This is because more cores mean it can tackle higher workloads in shorter amounts of time, meaning that it can deliver on performance. 

We recommend an Intel Core i7 due to how commonplace but reliable they are as high-performance CPUs. Since CPUs come in generations, you should look to the higher-numbered ones as they’re the latest and so, often, the best. This is why we’d advise you to get a 7th generation processor or above.

It should be noted that with computer parts however, that’s not always the guarantee that the latest piece of hardware is better than the last, especially as there may be compatibility issues. This applies to most computer parts, so choose wisely and approach new projects with some skepticism, making sure any future advancements are proven to be improvements on the last hardware before making the purchase.

Performance

The next big piece of hardware to consider when chasing performances that can handle machine learning and other AI activities is the GPU.  Whereas laptops intended for basic administration will want to focus more on CPU performance over the GPU, and laptops intended for gaming will be vice versa, machine learning computers benefit from both since the parallel computations GPUs allow are ideal. 

Some laptops don’t even retail with GPUs in them, so a good start would be to choose a laptop that does have one. GPUs can break your budget very easily, so be sure to stay within it if you have one whilst finding the best specs for you. High-end Nvidia GPUs would be our recommendation due to how ubiquitous the brand is and the quality of their performance, with our more specific recommendation being the RTX 2080 if you have the money to spend on it.

RAM is important for quick-loading data, which is faster when not performed on a secondary memory bank like an SSD or HDD. Loading such data in a time-efficient manner would improve the performance of a machine learning algorithm. As always, however, you won’t be needing too much RAM to get results from them, instead just make sure you’ve gotten fast ones. Compared to other computers, a machine learning laptop should still have a lot of RAM, at least 32GB of DDR4 RAM. Most laptops available should be able to handle 32GB quite easily.

Storage

As far as storage goes, machine learning datasets can number in the hundreds upon hundreds of gigabytes, so they can quickly fill up your laptop if they’re stored there even over a short time. For this you’ll absolutely want to seek out a laptop with 1TB of storage space. This can be an HDD, whose 1TB variants are cheaper, but the 1TB SSDs, or a combination of the two, are better since they are able to read and write data quicker than their hard drive cousins. 

No storage device on your laptop should fall under 256GB and should total 1TB or over, if you have a combination setup. Nothing is stopping you from having external storage devices for longer-term storage and is what you’ll want to do to stop the laptop from getting crowded. 

Battery Life and Portability

As for the less specialized, more standard concerns such as battery life and portability, more battery life can only be a plus when it comes to laptops. This applies even more in the context of machine learning systems which often need hours upon hours of trial and error to develop at their given purposes. With that said, the function of a laptop, whilst allowing for portability and ease of carry, can be a difficult choice for developing learning algorithms for that very same reason. You can’t leave an algorithm do its thing with a laptop like you can with a desktop setup, there’ll be distractions and standby periods whilst it’s packed away for travel.

Frequently Asked Questions

How much storage space is ideal for a machine learning laptop?

We’ve already established how intensive machine learning laptops will be on both performance and memory, and we’ve already established that we believe sub-256GB is too low when it comes to the storage in-built to the laptop itself Your laptop should hopefully have 1TB, but the real space comes in with externals. Depending on what exactly you’re doing on your laptop, 1TB should be fine, maybe two 1TB external HDDs if you can get them, and gradually increase your arsenal.

Is a GPU necessary for deep learning?

The size of the datasets involved in training a deep learning algorithm is enormous and so, in order to compute that data to an optimal degree, we highly recommend a GPU. You may be able to run certain instances without explicit problems, but your speed and processing capabilities will be drastically reduced.

Last update on 2020-07-15 / Affiliate links / Images from Amazon Product Advertising API

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