There are many factors that should be considered while talking about Best Laptops for machine learning. Rather than the laptops for everyday use, best laptops for machine learning should have a lot more specifications along with the best features. As machine learning is tough, so it requires tough as well as durable machines. With the increase in analysis platform worldwide, leading tech companies are integrating machine learning. What kind of machine should Students and beginners invest according to their budget who want to enter this domain? As there is a variety of best laptops for machine learning that we are going to talk about here.

For the projects you have in your mind, having a personal machine, you have to choose the mobility of your machine. As if you want to carry it around or with yourself, a laptop. A customized desktop is one of the handy ways to optimize workflow or for training the algorithms at work or at home.

While choosing the best laptops for machine learning, the following factors must be taken into consideration:-

Portability Processing power

Laptops having higher processing power gets heavier and in this way, their portability gets diminished.

The higher processing power shrivels the battery life of laptops and hence the portability gets diminished also in this case.
Portability would be of much value to you as a number of datasets have outgrown the handling power of a reclusive machine and for processing will depend upon you for getting access to Cloud.

The appropriate and ideal laptops which would be best for machine learning are going to be discussed here.
Requirements of the machine for best laptops:-


For RAM, my primary suggestion is a 16GB RAM but RAM of 8GB is also fine as 16GB RAM offers little advantages over 8GB RAM.


If you are interested in gaming or as well as you need a laptop for research purposes, advanced GPU is the most valuable one to get rely upon. For machine learning, the best recommended GPU`s are Nvidia GTX 1050-Ti and GeForce GTX1080 Ti.


For machine learning and research purposes Core i3, Core i5 and Core i7 laptops are available in the market. The 7th or 8th generation of Intel i5 is recommended. More powerful and high-performance laptops of i7 are also suggested.

Screen size

Best laptops for machine learning would be recommended with a screen size of 15-inches as this size would be extremely useful in investigating any kind of data as well as information.


Choose MacOS for steady and smooth execution but if you are used to Windows OS you can go with this as it all depends on your will.

Hard disk

The Hard disk of 256GB or 1TB is recommended as it all depends on the type of data you are using.
A motherboard should give you an option to add extra GPU`s and the recommended one which is 32PCI will give you this option.

Top Best Laptops for Machine Learning




1. Microsoft Surface Pro (5th Gen)


  • Its software is Windows 10 Pro, fastest surface Pro ever.
  • Intel 7th Gen Core i7 processor.
  • Battery life is 13.5 hours of video playback.
  • With Windows Hello face sign-in for enterprise security Enterprise-grade protection TPM chip is used.
  • With 1.73 lbs (784 g), it is the Lightest Surface Pro yet.
  • Comprises of storage of Solid state drive (SSD) 512GB.
  • Intel Iris Plus Graphics 640.
  • Consists of Ambient light sensors.
  • Exterior includes power key and volume key along with the Surface Pen (sold separately), Surface Mouse (sold
  • separately) and Surface Keyboard (also sold separately).
  • 5.0MP front-facing camera with 8.0MP rear-facing autofocus camera.
  • Dual microphones and 1.6W Stereo speakers.


  • Fastest one
  • Long battery life
  • Too expensive to buy





2. Acer predator Helios 300


Its software is Windows 10 Pro, fastest surface Pro ever.

  • Features a 2.8GHz,quad-core Intel Core i7-7700HQ processor.
  • Consists of a graphics card of Nvidia GeForce GTX 1060 (6GB GDDR5).
  • The hard drive of 1TB,256GB solid-state drive of your own choice.
  • Consists of 8GB RAM.
  • Battery life is up to 7 hours.
  • Windows 10 OS.
  • Widescreen IPS display of 15.6 inches full HD.
  • Consists of Red Backlit keyboard.
  • 6 GB of dedicated GDDR5 VRAM.
  • Weight 2.7 kg.



  • Performs well.
  • All games and All works are without lagging.
  • Provides real value for your money.
  • GTX 1060 is a real deal at this budget.
  • Average speakers.
  • Offers Better Display.





3. Acer Nitro AN515-51


Its software is Windows 10 Pro, fastest surface Pro ever.

  • Windows 10 Operating System.
  • NVIDIA GeForce GTX 1050 Ti.
  • Graphics memory capacity is up to 4GB.
  • Graphics memory technology is GDDR5.
  • Screen size is 39.6cm (15.6”).
  • LED backlight technology, full HD screen mode.
  • The display screen type is LCD.
  • 8GB is its standard memory and there is no memory card reader.
  • The total hard drive capacity is 1TB.
  • 256 GB of total solid state drive capacity.
  • Wireless LAN standard.
  • Maximum battery run time is 7 hours.


  • Easy storage upgrade.
  • No PWM-adjustment for all brightness levels.
  • Good battery life.

Dim display while battery-powered.




4. Microsoft Surface Book 2


Its software is Windows 10 Pro, fastest surface Pro ever.

  • 7th generation, Intel dual-core, Core i5-7300U processor.
  • 8GB of RAM and 256GB of solid-state drive (SSD) storage.
  • Windows 10 Pro OS.
  • Screen size is 13.5 inch.
  • Memory Graphics is NVIDIA GeForce GTX 1050 discrete GPU w/2GB GDDR5 graphics.
  • Battery life is up to 17 hours.
  • Ambient light sensor.
  • Built-in Xbox wireless.


  • Distinctive, well-constructed design.
  • Fast performance.
  • Best in a class battery.
  • Impressively light.
  • Expensive to buy.
  • Heavier than last year`s model.
  • Screen wobbles a bit.




5. HP Pavilion Power 15.6-inch laptop


Its software is Windows 10 Pro, fastest surface Pro ever.

  • It has a 2.5-GHz Intel Core i5-7300HQ processor.
  • RAM is of 12GB along with a 1TB, 7,200-rpm hard drive.
  • Consists of an Intel HD Graphics 630 GPU, Nvidia GeForce GTX 1050 GPU with 4GB VRAM.
  • A touch screen of 1920 x 1080.
  • Laptop`s weight is 1.81kg.
  • Windows 10 Home OS.


  • Good battery timing.
  • Slinky one.
  • Attractive design.
  • Comfortable keyboard.
  • Solid Graphics.
  • Overall performance.
  • Dim and dull display.
  • Sluggish SSD.
  • Weak audio system.





6. Apple 15” MacBook Pro



Its software is Windows 10 Pro, fastest surface Pro ever.

  • Consists of a touch bar with integrated touch ID sensor.
  • 15.4-inch LED-backlit Retina display with IPS technology.
  • 500 nits brightness with true tone technology.
  • Consists of a 2.2GHz 6-core Intel Core i7, Turbo Boost up to 4.1GHz, with 9MB shared L3 cache.
  • Storage capacity is 256GB and 512GB SSD.
  • Onboard memory of 16GB of 2400MHz DDR4.
  • Graphics of 2.2GHz as well as of 2.6GHz.
  • 4 Thunderbolt ports.
  • Wi-Fi wireless networking.
  • Full size backlit keyboard.
  • HD camera 720P face time.


  • High-resolution retina display.
  • Solid battery life.
  • Versatile Force touch.
  • Powerful speakers.


  • The battery is glued in place.
  • No SD card slot.
  • Expensive.




7. Lenovo Ideapad Full15.6-inch HD laptop


Its software is Windows 10 Pro, fastest surface Pro ever.

  • 8th Gen Intel, Quad Core i7-8550U.
  • Intel integrated graphics along with NVIDIA GeForce GTX1050 and AMD Radeon 540.
  • FHD of 15.6 and 15.6 HD.
  • 4GB onboard DDR4 with 16GB Intel Optane.
  • Windows 10 Os.
  • Standard backlit numeric keyboard.
  • Weight is 4.85lbs.
  • Battery life up to 6 hours, rapid charge, power off mode.


  • Designed to keep up with you.
  • Rapid charge any time.
  • Ample storage.
  • Rich, warm sound.
  • Slightly heavy.



Final Words:-

Machine learning is one of the toughest jobs which require laptops having the best features to make the job easier. By having one of the above laptops, one can test, train or build their machine learning models in a very short time. For machine learning, you can buy a mediocre as well as a great laptop on the basis of their performance. I hope you guys liked it. These are the 7 best laptops for machine learning that are discussed above. If you have any suggestions, do comment, please.

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