As a prospective or entry-level machine learning engineer, investing in a powerful laptop can help accelerate your academic and career growth. However, with the wide range of powerful laptops on the market, finding the best laptop for machine learning that is also affordable and has excellent performance can be quite challenging, if you don’t know the right places to look.
This guide on the best laptops for machine learning will help you discover the perfect device for any task. We will also detail the best laptops for machine learning under $1,000, in case you are on a budget. Further, in this article, you can learn what powerful combination makes a laptop an excellent choice for machine and deep learning.
How to Choose the Best Machine Learning Laptop
The perfect laptop for machine learning enables you to complete computational tasks and implement deep learning techniques with ease. To ensure you make the right choice when shopping for your next machine learning laptop, these are the factors you should consider.
Battery Life
The average battery life your machine learning laptop should display while working is five hours, because of the heavy lifting some of your projects might require. If you’re mostly on the move, then the perfect choice is a laptop with longer hours of battery life. This might mean a lower graphics processing quality but at least you won’t be out of battery while in the middle of a project.
Memory and Storage Capacity
Most of the projects you will work on will require you to install multiple applications with large file spaces and loading time. This will require a laptop with plenty of storage capacity for storing files to achieve clock speed computing. For best practice, your memory bandwidth should not be less than 8GB of RAM and 256GB of drive space, if you’re a beginner in the field.
CPU Processing Power
To enjoy an amazing performance when completing complex computations, you need a laptop with an Intel Core i7 or i9 processor or an AMD Ryden processor. These CPU cores were designed for multitasking and complex computing. They are the best options for machine learning professionals. However, if you’re just starting, an Intel Core i5 can also serve you well.
Screen Size and Screen Display
Your laptop’s external display should be at least 14 inches. For best practice, go for a laptop with maximum screen resolution and a 15-inch to 17-inch screen size. This may mean that you may need to sacrifice the laptop’s portability, but a larger screen size and superior HD display are necessary for completing tasks such as visualizing data sets and building models.
Dedicated Graphics Card and Performance Levels
The best graphics card and core level for machine learning laptops are the NVIDIA Geforce RTX or GTX, usually found in gaming laptops. However, if you can’t afford to customize your own gaming laptop, go for a laptop with an Intel Iris Core. These graphics cards ensure optimum performance when processing algorithms, as well as visualizing and rendering data models.
Operating System
The most popular operating system for machine learning is the Ubuntu-Linux operating system. This operating system supports multiple programming languages, has optimum security features, high performance, and is user-friendly. However, the latest upgrades in macOS laptops include more multitasking and security features. Windows is also a standard option for machine learning tasks.
How to Find Cheap Laptops for Machine Learning
- Take advantage of promo deals and special offers. One of the best ways of cutting down on the cost of a good laptop is through special offers and promos. You can take advantage of deals such as student discounts, holiday sales, coupons, and gift cards to access a wide range of laptops.
- Consider refurbished or used laptops. Purchasing used laptops is another way to cut down on costs. However, if you choose this method, ensure you properly check the external and internal conditions of the laptop with an expert eye before making the purchase.
- Go for older laptop models. Most times, newer models cost more. If you want a cheap laptop for machine learning, start with an older model. The downside to this is that you may not take home a powerful machine that can speedily accomplish your computational tasks in real-time. Make sure to compare features and check price ranges for several models.
The Best Laptops for Machine Learning in 2022
| Laptop | Manufacturer | Price | Features |
|---|---|---|---|
| Dell Precision 7760 | Dell | $5,033 | Intel Core Xeon CPU, NVIDIA RTX GPU, Windows 11 or Ubuntu |
| Lambda TensorBook | Lambda Labs | $3,700 | NVIDIA RTX 3080 Max-Q, Ubuntu, Intel Core i7, and 64GB of RAM. |
| HP ZBook Studio | HP | $3,459 | Intel Core i9, NVIDIA RTXA5000 or Geforce RTX 3080 |
| ASUS ROG Strix SCAR 17 G733 | ASUS | $2,200 | AMD Ryzen 9 5900HX, Geforce RTX 3080, 64GB of RAM |
| MacBook Pro 16” | Apple | $1,999 | M1 Pro and M1 Max chip, Liquid Retina XDR display, 64GB of RAM |
| Acer Nitro 5 | Acer | $980 | Quad-Core i5 processor, Geforce RTX, dedicated memory card |
| Lenovo Legion 5 Gen 6 | Lenovo | $920 | AMD Ryzen CPU, NVIDIA Geforce, 8GB of RAM, 512 GB storage unit |
| ASUS TUF Gaming F17 | ASUS | $914 | Windows 10 Pro, NVIDIA Geforce GTX, Intel Core i7 CPU |
| HP Envy x360 15” | HP | $900 | Windows 11, Intel Core i5, Intel Iris Xe graphics, 8GB of RAM |
| Dell Inspiron 15 | Dell | $869 | Intel Core i5, Windows 11, Intel Iris Xe graphics, 8GB of RAM, 256GB SSD |
Top Rated Laptops for Machine Learning: In Detail
Dell Precision 7760 Workstation
- Best for: Programming and visualizing data structures
- Price: $5,033
If you’re looking for a superior mobile workstation with AI and VR capabilities to aid you in writing functional programs and visualizing your data structures, the Precision 7760 workstation is an excellent choice. Although it’s the most expensive laptop on this list, it has a premium design with an Intel Core Xeon processor, NVIDIA RTX A5000 GPU, 32GB of RAM space, 512GB of storage capacity, and multiple connectivity ports.
Lambda TensorBook
- Best for: Deep learning
- Price: $3,700
The Lambda TensorBook AI workstation is a powerful workstation for all types of machine learning tasks. Although already well-designed by Lambda Labs, you can customize your laptop to suit your workflow needs. It was preinstalled with Tensorflow and PyTorch, two popular applications used for machine learning. It also comes with the NVIDIA RTX Super Max-Q.
HP ZBook Studio
- Best for: Rendering data models
- Price: $3,459
The HP ZBook Studio was built for running complex computations and applications. It has an advanced graphics processor that allows you to render your data models with ease. With 32GB of RAM, your mobile workstation is capable of simulating and building several projects sequentially. With the HP ZBook Studio, you may not need an external hard drive to store files.
Asus Rog Strix SCAR 17 G733
- Best for: Visualisation and software development
- Price: $2,200
Asus Rog Strix SCAR has a reputation for being one of the most preferred gaming laptops. However, this fantastic laptop can be used for machine learning because of its advanced computing features. As a machine learning engineer, you can accomplish a lot of computing tasks with its AMD Ryzen 9 CPU processor and its NVIDIA Geforce RTX 3080 GPU processor.
MacBook Pro 16”
- Best for: Data computing
- Price: $1,999
The MacBook Pro is a great laptop for machine learning because it was designed with superior computing power and speed to enable you to easily multitask. Along with a gorgeous screen size of 16 inches, it comes with an Intel Core i9 and an M1 Pro and Max CPU so you can code and build programs faster. It also has an amazing battery life, an LCD screen with external support, and 16-core GPU. Plus, users love the sleek design.
Best Laptops for Machine Learning Under $1,000
Acer Nitro 5
- Best for: Data rendering on a budget
- Price: $980
The Acer Nitro 5 is a notable laptop for performing some heavy machine learning tasks. It comes with a wide range of features that make it the ideal tool for developers and engineers alike. You’ll benefit from features like the NVIDIA graphics card, fingerprint reader, connectivity options, upgradable Windows OS, multi-touchpad, backlit keyboard, and 11 hours of battery life.
Lenovo Legion 5
- Best for: Multitasking
- Price: $920
The Lenovo Legion 5 is a great choice for machine learning as it comes with an optimal CPU and graphics core processor that makes multitasking seamless. You can accomplish a lot of data modeling tasks with this laptop. It comes with major features like the AMD Ryzen CPU, NVIDIA graphics, 8GB RAM space, and 512GB of drive space, to facilitate the development of artificially intelligent software programs.
ASUS TUF Gaming F17
- Best for: Visualizing data sets
- Price: $914
The ASUS TUF Gaming F17 plays a huge role in data visualization. Although it isn’t a lightweight laptop, it has amazing performance and is suited to most of the heavy tasks in machine learning computation and modeling. It comes with a Windows 10 Pro operating system, an Intel Core i7 CPU, an NVIDIA GTX, and large memory and storage units of 32GB and 1TB that offer plenty of space.
HP Envy x360 Convert 15
- Best for: Productivity
- Price: $900
The HP Envy x360 two-in-one convertible laptop was built to optimize your productivity. If you’re an AI/ML student, you can start your programming and software development journey with this laptop. Although it is sold at an affordable price, its features, particularly its 15.6-inch screen size, AI capabilities, and fingerprint reader make it ideal for different types of tasks.
Dell Inspiron 15
- Best for: People on a budget
- Price: $869
Even as the most affordable laptop on this list, the Dell Inspiron 15 is an excellent choice for machine learners engineers looking for budget laptops. Dell allows you to customize your laptop to suit your computing needs, as a way to optimize your funds. The tech specs for this laptop include an Intel Core i5 processor, a Windows 11 operating system, a 15.6-inch display size, good battery life, and 8GB of RAM storage space.
Should I Use a Laptop for Machine Learning?
Yes, you should use a laptop for machine learning. Having a laptop, even if it’s a regular laptop, can aid you in your computational tasks. Most laptops used for learning machine learning have been optimized with the same advanced data analysis and rendering capabilities that are common amongst desktops.
You can even enjoy the optimal performance with your laptop since you don’t need to use it with any external tools. It is also portable, meaning you can work on the go. A laptop also doesn’t need an external power supply to function as it is most times designed with excellent battery life. Having a great laptop for machine learning will help you get a job with the top machine learning companies.
Best Laptops for Machine Learning FAQ
Yes, machine and deep learning require a good laptop. Having a powerful machine for machine learning gives you the convenience that a desktop cannot give you. With a laptop, you can take your work anywhere you go. However, to boost your computing power, you need a portable laptop that’s designed with artificial intelligence features and a powerful processor, such as an Intel Core i7.
The best core processor for machine learning is either an Intel Core i7 or higher or an AMD Ryzen. An Intel Core processor gives you processing speed and performance but the parallel processing capability in AMD Ryzen ensures you can tackle multiple computational or design tasks at the same time.
Yes, Apple laptops are ideal options for machine learning tasks, plus they have a slim design. Apple’s MacBook Air and MacBook Pro were designed with the M1 Chip, known for their advanced computing power and processing speed. The M1 chip can be used to run deep learning frameworks and libraries effectively.
Artificial intelligence is a field and discipline that’s concerned with the optimization of computer systems and software to perform both light and heavy tasks commonly associated with human beings. Machine learning, on the other hand, is a branch of artificial intelligence concerned with the processing of algorithms and manipulation of data to automate predictive models.
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