Are MacBooks Good For Machine Learning in 2022?

MacBooks are popular in the programming community. And with Apple’s new silicon M1 chip they have even become more popular.

But how do they fair in machine and deep learning? Are MacBooks good for machine learning? Find out the advantages each MacBook provides in machine and deep learning tasks.

Is MacBook Suitable For Machine Learning?

Yes, MacBook is suitable for machine and deep learning. The introduction of M1 silicon chips has pushed the performance to greater heights. Moreover, MacBooks are greatly recommended by programmers because of the Unix environment.

Which Macbook Is Best For Machine Learning?

The MacBook Pro is a better choice than MacBook Air. Machine learning is a demanding task and requires sufficient processing power to train models. Below are the specs of the MacBook Pro:

  • CPU: M1, M1 Max or Pro (Up to 10-cores)
  • GPU: Up to 32-core GPU
  • RAM: Up to 64GB unified memory
  • Storage: Up to 8TB

These specs are more than enough to handle a lot of machine and deep learning model training. The downside is that the MacBook Pro is expensive.

Fortunately, you can look at the best laptops for machine learning guide to find affordable options. You can also buy a MacBook Air and make use of Cloud computing such as AWS, Google Cloud, etc.

Cloud computing services allow you to access powerful hardware over the internet. This makes it possible to train machine and deep learning models on not-so-powerful laptops.

Are M1 Macs Good For ML?

Yes, the M1 Macs are good for machine learning. The introduction of M1 chips in the Macs and MacBooks make it possible to train neural networks directly with accelerated performance.

Which Laptop Is Best for Machine Learning?       

Generally, laptops with high-performance multi-core CPUs, powerful GPUs, at least 16GB of RAM, and a large amount of storage are the best for machine learning.

The best laptops for machine learning depend on the size of neural networks to be trained.

  • Small neural networks don’t require powerful laptops.
  • Medium neural networks require decent hardware.
  • Large or complex neural networks require powerful laptops to be trained.

Moreover, cloud computing allows you to set up small-large neural networks without requiring powerful hardware.

Does TensorFlow Work On Mac M1?

Yes, TensorFlow v2.5 natively supports Apple M1. You can leverage Apple’s TensorFlow-metal Pluggable Device in TensorFlow for accelerated training on Mac GPUs.

Is MacBook Air Good For Machine Learning?

For directly running and training neural networks, the MacBook Air isn’t good. However, the MacBook Air is a great option if you have access to a remote supercomputer or cloud computing.

This allows you to create, model, and confirm neural network models from your MacBook Air.

Then using powerful hardware of the remote computer or processing power of cloud computing to train the neural models.

The MacBook Air even becomes more important when on a budget. Cloud computing is fairly cheap allowing you to take advantage of the massive processing resources.

Using cloud computing for training neural network models

Final Thoughts

The MacBook Pro and MacBook Air are both great for machine learning. The MacBook Pro has the advantage of training large/complex neural networks locally.

Whiles the MacBook Air combined with cloud computing is a budget option and a great entry to machine learning.

As a lover of technology. Kelvin spends most of his tinkering with stuff and keeping up to date with the latest gadgets and tech.

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