Best Laptop for Machine Learning

mac laptop

Machine learning is a field of artificial intelligence that has drawn so much interest in the technology world. The field of machine learning studies and develops algorithms that learn from data input and accurately perform certain repetitive tasks just like or better than human beings. Whether you are a learner undertaking machine learning training and/or projects, an entry-level machine learning engineer, or a seasoned professional in the machine learning field, there is nothing as important as investing in the right tools of the trade for your job, and this includes a laptop.

You are only as effective as the laptop you invest in for your job. When buying a laptop for machine learning, you need to consider several factors which we shall be discussing below. Fundamentally, you want a laptop with the capacity to manage large datasets and other machine learning tasks. This means that you need a laptop with a powerful processor, GPU, and enough RAM. At the core, these three factors enhance your speed and performance, and this is what you need.

Yet still, there are other factors that you need to consider when getting the best laptop for machine learning.

What should you bear in mind when purchasing a laptop for machine learning?

The best laptop for machine learning will enable you to effectively carry out computational tasks, build, and implement ML algorithms and techniques. For you to make an informed decision, here are the factors that you should consider.

  1. The CPU and the processing power

Ideally, the latest generation processors are known to be more powerful compared to their predecessors. Thus with technological advancements, ML demands for processors go hire since technically computations become more complex. At the least, an Intel Core i7 processor (7th generation) or higher will serve you well for machine learning computational processes thanks to its remarkable speed and performance. Alternatively, you can get AMD Ryzen processors as they are equally powerful enough to run complex parallel ML processes hence high performance. For beginners, however, an Intel Core i5 CPU will suffice

  1. The RAM and Storage Capacity

RAM (Random Access Memory) refers to the amount of short-term memory that a laptop or a computer operates with alongside the longer-term memory storage, usually a Hard Disk Drive (HDD) or Solid State Drive (SSD) depending. A larger RAM means that your laptop should be able to process larger datasets faster. A RAM of 16GB or higher is recommended. Tasks like training models may require higher capacity, like 32GB RAM. You could also opt for 8GB RAM, but this will be effective when most of your processes are executed in the cloud.

For long-term memory storage, a minimum of 1TB HDD or 256GB SSD should accommodate your large datasets.

  1. GPU

Another crucial factor to consider is the GPU (Graphical Processing Unit). A GPU card is a microprocessing chip that processes graphics and algorithms and renders data models. With the use of neural networks and heavy computations in deep learning, a GPU card becomes necessary. GPUs can handle multiple processes in parallel without compromising performance and are considered to be higher performing than CPUs. They have higher memory bandwidth, numerous core units for a faster processing speed, as well as a high video RAM.

The latest generation NVIDIA GPUs like GeForce RTX is often preferred as their APIs and frameworks are compatible with most deep learning libraries like TensorFlow. Intel Iris Core GPU is also a good cheaper alternative to NVIDIA.

  1. Operating System

Linux is more often preferred over other operating systems. This is because it supports the most popular programming languages, is user-friendly, has high performance, and is well secured. Still, Windows and macOS are good options when running on the Virtual Linux Environment.

  1. Battery Life

When considering battery life, it is important to bear in mind the factors that affect battery life, including high processing power. Nevertheless, you still need to look for a battery with long life. To preserve battery life, you could opt for lower graphics processing and have your battery take you right to the end of your task.

  1. Display

A larger screen size, perhaps 15-inches or 17-inches is better than a small screen that allows for convenient portability in a laptop. Consider a large screen size that allows for maximum resolution, as this is important for visualization tasks.

  1. Portability

As we have seen above, you may have to choose between a larger display or a smaller one on a portable laptop. Also, consider other factors that affect the weight of a laptop, including a higher RAM. Portability is important if your job involves moving from place to place.

Best laptops for machine learning

Here are some good laptops that you can consider for your machine learning tasks.

Laptop Model CPU RAM GPU Storage Display
ASUS ROG STRIX G Intel Core i7-9750H processor 16GB DDR4 NVIDIA GeForce GTX RTX2070 1TB SSD 15.6-inch FHD
Razer Blade Pro 17 2.6GHz Intel Core i7-9750H 16GB 6GB NVidia GeForce RTX 2060 512GB SSD 17.3-inch FHD with 1920 x 1080 maximum resolution
Acer Nitro 5 9th Gen Intel Core i7-9750H 16GB DDR4 NVIDIA GeForce RTX 2060 256GB NVMe SSD 15.6″ Full HD Widescreen
MSI GS65 Stealth-002


8th Gen Intel Core i7-8750H 32 GB RAM NVIDIA GeForce RTX 2070 512 GB SSD 15. 6″ Thin Bezel FHD Display
ASUS ROG Zephyrus GX501 Ultra Slim


8th generation Intel Core i7-8750H


16 GB DDR4 NVIDIA GeForce GTX 1080



15.6” FHD


Acer Predator Helios 300


8th generation Intel Core i7 16 GB DDR4 NVIDIA GeForce GTX 1060 256 GB SSD HDD 15.6-inch FHD
TensorBook by Lambda 8th generation Intel i7-8750H 32GB NVIDIA 2070/2080 (8GB) 1TB NVME SSD 16.1″ FHD


Machine learning professionals are constantly on a quest to get the best machines for their ever-evolving machine learning roles. As we know, machine learning is a field that is still evolving and promises many more advancements and innovations in the near future. High-performance laptops with a good memory, faster processing speeds, and powerful processors are available for machine learning tasks. Also, if portability is not a matter of great concern to you, you may consider a custom-built desktop computer for your work. The most important thing to bear in mind is the graphics, hard drive space, and processor.

Hi, I'm Raj Hirvate and I am a Tech Blogger from India. I like to post about technology and product reviews to the readers of my blog. Apart from blogging i'm a big Anime fan I Love Watching Naruto, One piece and Death Note.

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