In Software Development
So you need to decide which computer suits you best, a mobile laptop that you can carry with you or a stationary machine for developing and training algorithms at home or at work.
Management
With the rise of analytics platforms in every sector, leading big tech companies and startups are integrating machine learning and deep learning into their existing system. This led to the rapid deterioration of computers due to the increasing load on the computer hardware.
The use of machine learning and deep learning has led to a big revolution in the hardware required for these installations. But what about students and newbies who are trying to get into the AI sector, what kind of computer should they get based on the budget they have? We present various options that are available in the market.
What are the minimum requirements for a ML laptop?
Note: Only Nvidia GPUs have the CUDA extension which enables GPU support for Tensorflow and PyTorch.
Budget Laptops
You can also find budget laptops with CUDA Nvidia GPU support for deep learning. Gaming laptops with these specs aren't really for gaming, they can also be used for deep learning.
It is possible to build your own computer for a lower price compared to these expensive laptops. This article will provide you with a summary of how to set up a machine for deep learning. As technology advances, GPU prices skyrocket with the addition of new Nvidia Tesla GPUs.
What are external GPU docks?
An external graphics processor, in addition to your existing laptop, you can buy an external graphics dock extension, such as the ASUS ROG HD Graphics Station for iPod. Add-ons can be purchased based on your specifics.
With one of these laptops, you can build, train, and test your own deep learning models in a short amount of time. When it comes to deep learning, it is necessary to tune the hyper parameters, which is a tedious and time-consuming task, it is desirable to have a powerful machine to save nerves and time.