Should Data Scientists Care About the New M1 Pro and M1 Max MacBook Pro? (2024)

FAQs

Should Data Scientists Care About the New M1 Pro and M1 Max MacBook Pro? ›

Data science libraries such as TensorFlow and PyTorch benefit from more CPU cores, so the upgrade from 4 high-performance CPU cores in the original M1 to 8 in the new M1 Pro/Max will be definitely good for doing data science tasks.

The MacBook Air M1 is a powerful and versatile laptop that is well-suited for data analysts. Its M1 chip, designed specifically for Mac, delivers incredible performance and speed, making it ideal for handling large data sets and complex analyses.

The Apple MacBook Pro is not just the ultimate laptop for data scientists, but it's also one of the our favorite laptops ever.

On the M1 Pro, you get up to 16 cores for your graphics processing. On the M1 Max, you're going to get up to 32 cores! That's a big difference, especially for those playing video games, editing videos, or doing some kind of animation. Another difference you'll see comparing M1 Pro vs M1 Max is memory bandwidth.

Apple MacBook Pro

The Apple MacBook Pro, powered by the M1 chip, offers incredible performance and energy efficiency. It's the go-to choice for data analysts who prefer macOS.

Data analysis requires a lot of memory. To handle large datasets and complex calculations, you need a laptop with enough RAM. It's recommended to have at least 16 GB of RAM, but more is better.

Apple's press release for the new M3 MacBook Air includes a bold claim, calling the machine the “world's best consumer laptop for AI.” The claim comes ahead of WWDC 2024, during which Apple is expected to announce a slew of new artificial intelligence features across all of its platforms.

1. Apple MacBook Pro (16-inch) When it comes to data engineering, the MacBook Pro has long been a favorite among professionals, and for good reason. The 16-inch model, released in 2021, packs a serious punch with its M1 Pro or M1 Max chip.

M1 Max features the same powerful 10-core CPU as M1 Pro and adds a massive 32-core GPU for up to 4x faster graphics performance than M1. With 57 billion transistors — 70 percent more than M1 Pro and 3.5x more than M1 — M1 Max is the largest chip Apple has ever built.

The new MacBook Pro delivers game-changing performance for pro users. Choose the powerful M1 Pro or the even more powerful M1 Max to supercharge pro-level workflows while getting amazing battery life.

Is M1 Max more powerful than Mac Pro? ›

M1 Pro offers up to 200GB/s of memory bandwidth with support for up to 32GB of unified memory. M1 Max delivers up to 400GB/s of memory bandwidth — 2x that of M1 Pro and nearly 6x that of M1 — and support for up to 64GB of unified memory.

What CPU is best for data science? The two recommended CPU platforms are Intel's Xeon W and AMD's Threadripper PRO. Both of these offer high core counts, excellent memory performance & capacity, and large numbers of PCIe lanes.

More Data, More Storage

This is a little tricky, as the minimum storage space you need is 512 GB, while recommended is 1 TB. More importantly, you should go for SSD. In case your budget doesn't allow an SSD with 1 TB or higher capacity, then choose 512 GB. That's because HDDs (Hard Disk Drives) are much slower.

What CPU is best for data science? The two recommended CPU platforms are Intel's Xeon W and AMD's Threadripper PRO. Both of these offer high core counts, excellent memory performance & capacity, and large numbers of PCIe lanes.

Better and diverse career opportunities:

IT sector demands professionals with diverse skill sets. While MCA opens jobs mainly in the software development industry, M.Sc. (IT) prepares them for roles in the IT industry, software development, cyber security, data science, R&D labs, and various segments of the IT sector.

In a detailed blog post from May 2022, Sebastian Raschka, PhD talks about using the M1 MacBook Air. He says it's fast for some jobs, but not ready for the more complicated deep-learning tasks. He thinks it has a lot of potential but needs more time to grow.

working with very large databases, but most programs shouldn't require more than 8GB RAM. on the type of coding work that you're doing. remote access, then 256GB should cover all your needs without issue. that these specs will suit your needs just fine.