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Desktop Vs Laptop: Ideal Device for Machine Learning

Desktop Vs Laptop: Ideal Device for Machine Learning

by October 4, 2022 0 comments

Machine learning is one of the hot cakes right now among young professionals. Most coders are considering Data Science, Deep Learning, Machine Learning, Artificial Intelligence, etc. as their career choice.

To achieve your dreams, you need an efficient companion that can handle heavy workloads while processing different data sets and running diverse apps simultaneously. Selecting the best match for the job is challenging because you have to consider several factors including processing power, graphics processing capability and portability among others.

In terms of hardware, you need a latest CPU, Intel Core i7 or i5 with Turbo Boosts along with a dedicated GPU for handling graphics for simultaneous computations. You also need ample RAM, 16 GB or higher for more Machine Learning tasks. When you think of Data science and Machine Learning, you should go for higher capacity storage space as you would deal with numerous heavy data sets.

Now that we’ve sorted out the configuration, let’s think about the form factor – some ML engineers would rely on a desktop while others would consider laptop as a better choice. Let’s understand how to choose the right form factor.

Desktop vs Laptop

The big advantage of using a desktops for ML work is that they’re far more upgradable than laptops. You can replace your old GPU with a new and more powerful one, which is not possible in laptops. You can add more RAM, storage, and other components. So, if you have multiple or large ML projects to work on, and your work doesn’t require you to travel, then desktop is the best option without a doubt. You’ll get a much larger screen to work on, along with a full-sized keyboard and a mouse to make it more comfortable. Moreover, as all components in desktops are bigger, their performance is also more than laptops. ML is compute-intensive and can consume a lot of power. PCs normally have a large enough power supply to provide the required power for the work.

Though laptops are evolving and becoming increasingly powerful, a fully loaded desktop will still give you better performance. So, if performance is a concern and portability isn’t, then desktop is the way to go for serious ML work.

Laptops are of course the obvious choice if your work requires you to travel a lot, like meeting a lot of clients to give demos. If you’re just starting out on ML, then also laptops make more sense to at least start getting the hang of things. You don’t need to invest extra on a powerful desktop when you don’t need it. In fact, many students even opt for a gaming laptop with an additional GPU, because they’d like to be able to use it for both work and gameplay.

Conclusion

Choose the device based on your nature of work. Vendors like HP for instance, are providing systems targeted specifically at data science and ML professionals. The Z lineup of systems by HP are the right choice for ML work, be it desktop or mobile workstation. They are designed to deal with heavy processing, and if you choose the right machine, they can outperform anything else while processing different data sets and running various apps simultaneously.

Click here to visit the HP Online store for some really great deals on the products discussed above.

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