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Our 5 Best Laptops for Machine Learning

Machine Learning and Deep Learning are very demanding in terms of hardware – especially Deep Learning. That’s why most people generally prefer desktops when it comes to machine learning, but what if you need a laptop? If you’re like us, and you’d much rather use a laptop for all your machine learning needs, then you may as well get the best available.

So, without any further ado, let’s take a closer look at what we consider as the best laptops for machine learning!

Things To Consider Before Buying The Best Laptop For Machine Learning

Before you even start considering which laptop to choose, there are a few things to keep in mind at all times. Things that we need to understand to ensure the laptop we’re considering is the right choice for our specific needs. The individual components of a laptop are extremely crucial and can seriously impact how efficient it is for Machine Learning and Deep Learning. 

With that in mind, let’s take a look at some key aspects to always consider:

  • Budget: Start by limiting your options down to whatever you can afford. After all, there is no point in checking out laptops that you can’t buy anyway. The minimum budget should be about $1000 while the ideal laptop is closer to the $3K mark. If you can’t afford the minimum, we wouldn’t recommend going any lower than $800-900!
  • CPU: More cores are generally better. Since laptops generally don’t have as many cores as desktops, aim for at least a Core i7 or a Core i9! And under no circumstances get anything weaker than a quad-core i5! (Some older i5s come with 2 cores)
  • GPU: A GTX 1050 is the bare minimum. Avoid integrated graphics like the plague. Ray tracing is useless for machine learning – which means that RTX cards aren’t all that useful for us. But, you can still take advantage of their extra power. 
  • Storage: SSDs make a world of difference in performance and are relatively cheap. If your laptop of choice doesn’t come with one, do seriously consider swapping out the HDD for an SSD!
  • RAM: 8 gigabytes is the bare minimum, 16 is the sweet spot, and 32 is the future-proof option.
  • Portability: Screen size, slimness, and overall weight are a few things to keep in mind if portability matters to you
  • Battery life: Sometimes you just need to work on the road. So, pay attention to the average-rated battery lifespan that manufacturers provide (Battery size isn’t always a decent measurement as some laptops/components are more power-hungry than others)

Our Top 5 Laptops For Machine Learning

Now that you have a better understanding of what to look for in a new laptop specifically tailored towards machine learning, it’s time to see what we’ve chosen as our top five picks that are available this 2020.

The following laptops have been carefully considered to ensure that all of them showcase excellent price, performance, and overall user experience – not to mention the above considerations as well.

1: Best Laptop for Machine Learning on a Budget: Dell Inspiron i5577

At about $800 (Depending on the time of purchase, various discounts, and other contributing factors that affect pricing), you may feel like this is an expensive laptop. But, in fact, if you want the best laptop for machine learning on a budget, then we wouldn’t recommend spending anything less than that!

  • CPU: Intel Core i5-7300HQ
  • GPU: Nvidia GTX 1050 4GB
  • RAM: 8GB
  • Storage: 256GB SSD
  • Display: 15.6 LCD Display at 1920 x 1080
  • Battery: 6-cell 74WHr – 7 hours of average use (According to Dell)
  • Weight: 5.5 pounds

It comes with a GTX 1050, a 7th gen Core i5, 8 gigs of RAM, and a 256GB SSD! As we mentioned above, these are the bare minimum requirements for Machine Learning and Deep Learning. 

In fact, if you can afford to do so, we’d recommend spending a bit more and going with at least a Core i7. 8 gigs of RAM are also going to be insufficient – depending on what you’ll be doing and the level of multi-tasking. But, thankfully, Dell gives us the option of adding as much as 32GB of RAM down the line. 

Speaking of upgrades, if you are too scared to “Get your hands dirty”, consider asking a professional to install the RAM later. After all, RAM modules aren’t that expensive anymore. 

If you care about content consumption, then do keep in mind that you get a 15.6″, LCD display (And rather thick bezels), a GTX 1050 for entry-level gaming, 3x USB 3.0 ports, and an average battery life of 7 hours!

Pros: 

  1. Very cheap (Compared to other options)
  2. Relatively small/compact
  3. A bit of room for upgrades (RAM)

Cons: 

  1. Not the best option for gamers (The 1050 is good enough for entry-level gaming at low graphics, low resolution. Maybe some MOBAS as well. But that’s about it.)
  2. Barely acceptable for Deep Learning
  3. Mediocre display
  4. A few complaints about the build quality and Dell’s warranty policy

2: Value for Money: MSI GS65

This is the sweet spot in terms of value. With a 6-core Core i7, an RTX 2060, 16 gigabytes of RAM, and a 512GB SSD, the MSI GS65 is a laptop that is capable enough for both Machine Learning and Deep Learning. 

  • CPU: Intel Core i7-8750H
  • GPU: Nvidia RTX 2060 6GB
  • RAM: 16GB
  • Storage: 512GB Nvme SSD
  • Display: 15.6 LCD, 144Hz, 1920×1080
  • Battery: 80Wh battery with a maximum endurance of 8 hours and an average of 4
  • Weight: 4.19 pounds

If you’re interested in content consumption as well, then do keep in mind that you’re getting a 15.6 inch, LCD display with a refresh rate of 144Hz and a resolution of 1920 x 1080 along with an RTX 2060 for mid-range gaming. 

Other than that, you can get up to 8 hours of battery life (Depending on the kind of usage – power-demanding tasks drain the battery much faster), thin bezels, along with a sleek design as well!

The laptop comes with Windows 10 pre-installed – which is something to be expected at this price point. Last, but not least, you can also install up to 32 gigabytes of RAM down the line. According to MSI, only a single slot is occupied with a 16-gigabyte stick. So, all you’re going to need is an additional 16GB module. 

Pros: 

  1. Relatively, slim, lightweight, and compact
  2. Good value for money
  3. Decent for mid-range gaming
  4. High refresh rate display

Cons: 

  1. The RTX 2060 can’t fully take advantage of the high refresh rate display (Struggles to reach 144FPS in most titles – except a few competitive ones, which is where it matters the most, of course)

3: The Decent Mid-Ranger: Gigabyte AERO SA-7US5130SH

This is another great mid-range choice that’s not only a great option for Machine Learning, but also for content consumption. Inside it, you’ll find a 9th gen Core i7, a GTX 1660 Ti, 16 gigs of RAM, and a 512GB Intel 760P SSD as well!

  • CPU: Intel Core i7-9750H
  • GPU: GTX 1660 Ti 6GB
  • RAM: 16GB 
  • Storage: 512GB SSD
  • Display: 15.6 AMOLED display at 3840×2160 (4K)
  • Battery: 94.24Wh – 8 hours of average usage
  • Weight: 4.4 pounds

The 1660 Ti may be slightly weaker than the RTX 2060, but it doesn’t make a whole lot of difference for non-gamers. And even for those who do game on it, we’re usually talking about a difference of 20 FPS or so (Even fewer on higher resolutions). 

Other than that, one thing that sets this option apart from other mid-rangers is the 4K, AMOLED display! If you don’t find this to be the best laptop for Machine Learning, then you’re at the very least going to enjoy watching movies and playing games on it. 

As far as battery life is concerned, you can get an average of 8.5 hours on it – depending on the kind of usage, of course. 

Pros: 

  1. The best option for content consumption (4K, AMOLED display)
  2. Big battery
  3. Decent for mid-range gaming
  4. RGB keyboard – if you’re into that

Cons: 

  1. The 1660 Ti version can’t fully take full advantage of the 4K screen in terms of gaming (And playing at a lower resolution may make some games feel blurrier compared to a native 1080P experience)

4: Best Laptop for Machine Learning (High-End): ASUS ROG Zephyrus S GX701

This is one of the most ideal options for Machine Learning. With a hexa-core i7, an RTX 2080, 16 GB of RAM, and a whole terabyte of SSD storage, there isn’t a whole lot of room for improvement here. 

  • CPU: Intel Core i7-8750H
  • GPU: Nvidia RTX 2080 8GB
  • RAM: 16GB
  • Storage: 1TB Nvme 
  • Display: 17.3 LCD IPS display at 1920×1080
  • Battery: 76 Wh – 3.5 hours with average use
  • Weight: 6 pounds

And while Asus hasn’t mentioned anything about RAM upgradeability, there is a good chance that you’ll be able to get up to 32 gigabytes with the necessary swaps. 

Apart from Machine and Deep Learning, the ROG Zephyrus is also a superb choice for gaming! After all, we’re looking at an RTX 2080 along with a 17.3 inch, 144Hz, G-Sync certified display. 

Other than that, there’s also an RGB keyboard, the option of switching between integrated and dedicated GPUs for better battery life or performance, support for remote charging with a power bank, and much more. 

If there’s one downside, then that’s definitely going to be the size. At 17.3 inches, it’s not the most portable choice around. But, in the end, this is a matter of personal preference. 

Overall, at this price point, you get the whole package – almost. 

Pros: 

  1. By far the best option for those who are interested in gaming
  2. Big, high refresh rate with GSync
  3. Comes with some of the most powerful components 

Cons: 

  1. Expensive
  2. Big and a tiny bit heavier compared to our other options

5: Best Overall Laptop for Machine Learning: MSI P65 Creator-654

This is as close as you can get to the ultimate laptop for Machine and Deep Learning. The only small sacrifice is that instead of an RTX 2080, you get an RTX 2070 – which is still crazy-powerful, of course. 

  • CPU: Intel Core i9-9880H
  • GPU: Nvidia RTX 2070 8GB
  • RAM: 32GB
  • Storage: 1TB SSD
  • Display: 15.6 LCD display at 3840×2160 (4K)
  • Battery: 6.5 hours with average usage (MSI doesn’t mention anything about battery size)
  • Weight: 4.19 pounds

Other than that, the laptop comes with 32 gigs of RAM out of the box, a Core i9, and a 1TB NVMe SSD! If that’s not enough for you, then we don’t know what it’s going to take. 

It goes without saying that at this price point, this is a machine that’s not just suitable for work, but for pretty much anything else as well. 4K display (15.6 or 17.3 inches), RTX 2070 for high-end gaming, Thunderbolt 3 connectivity along with a couple of USB 3.2 ports, a premium build, and more. 

As per usual, battery life can range anywhere from 2-3 hours all the way to 8 or even more depending on the kind of usage. Gaming and Deep Learning are two of the most demanding tasks – which is why we’d highly recommend keeping it plugged in with cases such as these.

Pros: 

  1. Offers the most powerful CPU that you can get
  2. 32GB of RAM out of the box
  3. All around a good choice for gaming, Machine Learning, and anything in-between

Cons: 

  1. Expensive
  2. Doesn’t offer the RTX 2080 (Considering the fact that it offers the most powerful components in almost every other category)

Best Laptop for Machine Learning: Wrapping Up

So, when everything is said and done, which laptop should you pick? Well, to wrap things up as quickly as possible, here is the TL;DR: 

  1. Dell Inspiron i5577: Best affordable choice. We wouldn’t recommend buying anything cheaper than that. Even this is barely acceptable
  2. MSI GS65: Best value for money on the mid-range category
  3. Gigabyte AERO SA-7US5130SH: Superb for those who want their laptop not only for Machine Learning but also for watching movies or anything that requires a great display (AMOLED)
  4. ASUS ROG Zephyrus S GX701: In addition to being quite possibly the best laptop for Machine Learning, the Zephyrus S is also one of the best, if not the best choice for gamers
  5. MSI P65 Creator-654: Offers the most powerful processor out of the bunch while also coming with 32 gigabytes of RAM out of the box. The only downside is that it sacrifices a tiny bit of GPU power – quite possibly the best (And most expensive) overall laptop for Machine Learning

About the author

Charlie Noon

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