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Disciplines such as deep learning, artificial intelligence, and machine learning can be practiced only with the help of powerful machine learning laptops. We are talking about machines that often need to crunch large quantities of data over a short period. Here is a guide designed to help you choose the best possible laptop for machine learning.

General Processing Unit (GPU)

The best GPUs for machine learning feature a high number of cores and a high memory bandwidth. It is super important to have as many cores as possible when dealing with large amounts of data. In addition, the processing power of the GPU is of great significance if computation time matters, which is usually the case for machine learning.

NVIDIA GPU is often recommended because it’s compatible with deep learning networks like PyTorch and TensorFlow. GeForce RTS is an NVIDIA GPU that features AI-enabled Tensor cores and a Turing architecture. There aren’t any better GPUs out there for deep learning.

Random Access Memory (RAM)

The more RAM, the more data your machine can handle, which translates to faster processing. Having plenty of RAM installed means that you can handle other tasks while the model trains. 8GB of RAM is the bare minimum, but 16GB and above is required for machine learning tasks.

CPU

The minimum here is Intel Core i7 featuring Turbo Boosts. But for best performance, you need at least a 7th generation CPU. If you choose a desktop, selecting the proper combination of GPU, CPU, and motherboard is essential. In one such case, the number of PCIe lanes is super-important. PCIe lanes are responsible for transferring data from the CPU RAM to GPU RAM. Typically, four to sixteen lanes are sufficient for machine learning tasks.

Storage

Deep learning datasets are getting bigger and bigger. Because of that, a high storage capacity is e necessity. On the other hand, SSDs are not as expensive as they once were, so there is no point in investing in an HDD. If you are really on a tight budget, then a hybrid of the two is an option. But know that a hybrid is still somewhat slower than SSD. Experts usually recommend SSD for faster performance.

Bottom Line

In this article, we have mentioned the essential components to configure a decent machine learning laptop. Getting more of everything is a good idea, as long as your budget allows it. The alternative to a laptop is setting up a deep learning system in the cloud. Cloud services such as the Google Cloud, AWS, and Azure can train your models much faster than your laptop.

So, a laptop for machine learning is a good idea if you are at the start of your machine learning career and still learning how everything works. Once you get more serious and start working on real projects, you need to hit the cloud. That’s how professionals train their machine learning models, and you should do, too.

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