Best Laptops for Data Scientists (including AI & ML)

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► Timestamps

00:00 Intro
02:12 Display
03:11 Chassis
03:34 Keyboard
04:10 Trackpad
04:19 Processor
05:39 Configuration
06:16 Battery Life
07:10 Minimizing Distractions
07:45 AI & Machine Learning Requirements
11:05 Laptop Recommendations
11:53 Yoga Slim 7i Aura Edition
12:41 MacBook Air 15
13:32 ProArt P16
14:20 Yoga Pro 9i
14:45 IdeaPad Pro 5i
14:58 MacBook Pro 16
15:51 Legion Pro 7i
16:34 Eluktronics Hydroc
17:03 Titan 18HX
17:19 Outro

As an Amazon, Lenovo, Best Buy, B&H, Dell, and HP Associate I earn from qualifying purchases

#best #new #laptop #ai #datascience

[wgm]

This type of video demonstrates exactly why the justjosh channel is on another level to other tech/laptop channels on youtube

[MayurGarg]

I am a professional Data Scientist and here are the things that I prefer in a laptop:

Minimum requirements: 15+ inches and 16GB RAM
Preferred: 32 GB RAM

Case dependent:
- If you use something like Excel (or other Office Suite) or in memory analytical libraries like pandas a lot, prefer laptops with a high single core performance. Also, choose the RAM based on how much data you process at once.
- If you perform distributed analysis or build CPU based models (like scikit-learn), prefer high multi-core performance and high thread count.
- For deep learning models for tabular data, I would prefer faster GPUs over VRAM. But depends on the scale of the data.
- For deep learning models for images or LLMs, I would prefer GPUs with high VRAM over raw GPU performance. My suggestion would be 8GB+. You could get a lot more done with a higher batch size.

- A good keyboard is good to have but should not be the main buying decision imo unless you are a super Excel user or something. This is since most programmers, including myself, spend most of the time reading code and data and a lot less typing.
- If you use a laptop for professional use, most likely you would be using a desk style setup. In that case, a long battery life and a nice trackpad is nice to have but should not be the focus. In a desk setup, it is better to plug in the laptop and use a mouse.
- For deep learning models, I prefer Nvidia GPUs since I feel like it is more supported and easier to set up.
- Screens are subjective. Choose the screen type based on your budget and how likely you are to use the laptop for other stuff (gaming, Netflix, YT). Choosing the screen specifically for coding is a bit overrated imo.

Bonus:
- If you use Excel a lot or any IDE (VS Code, PyCharm, etc.) a lot, buy a wide screen monitor. It is a game changer for development.

These are just my opinions and preferences.

[jeffrey]

DS here who managed to get an M2 Max with 96GB at work. Love the device. But don't kid yourself. You will not do any significant LLM training on this thing either. Its fine if you stay below that 1B weights range I would say.
If you think about buying something for personal use just get a cheaper device + setup a local workstation and ssh into that. Will also help you build up your skills

[PiracyAgreement]

An underrated feature for Excel heavy users is the full-size arrow keys.

For me, it's a non-negotiable.

[Hundredthldiot]

I'm really not convinced about the case for LLMs on laptops, or even desktops. I don't work in AI, but conventional software engineering went through this over a decade ago with the transition from local and on-premise CI builds (e.g. Jenkins) to cloud CI (Travis, GHA and so on). I think it's beyond the scope of this channel, but if I was making this decision I would start with "what is it going to cost me in terms of cloud compute, and so what's the ROI period for a more expensive laptop capable of running the same work locally?". There are other benefits of running stuff on cloud, like greater flexibility in terms of instance sizing, and simply being able to close your laptop and let stuff run while you do other things.

[GunzyTech]

As a writer who trains our company's in-house AI models, I make it a point to watch each of these videos. Even when the content doesn't directly relate to my work, I find that there's always valuable insight for my laptop search.

[akin]

As a former Insurance underwriter turned IT analyst, most of the time you are in an office or working from home. 300 nits of brightness are perfectly fine. Lenovo ThinkPad T14 GX, Dell Latitude 7XXX, and HP EliteBook 840 GX will be the laptops assigned to most data analyst workers by their company.

[Mike-jbxe]

Never think a laptop is good for AI / ML, you don't want a long running task living in your laptop, and make everything else awkward (annoyed by the heat but can't do a pause / resume, accidentally close the lid, etc). Would rather build and ITX pc and ssh into it.

[franciscowilhelm]

Using personas to calibrate the recommendations to prototypical use cases. Excellent quality video!

[lhl]

Since I just spent quite a bit of time doing research and running tests, I just want to note that the M4 Max 40CU (top of the line), sadly only has 34.08 TFLOPS of FP16. This is roughly equal to a desktop RTX 4060 in terms of compute. A mobile RTX 4090 (which is pretty cut down from the desktop version) will still have twice the Peak FP16 Tensor TFLOPS w/ FP32 Accumulate (also, 264 INT8 TOPS for quantized inference). Based on 40 RDNA3.5 CUs, Strix Halo should have just shy of 60 FP16 TFLOPS (but only 256GB/s of MBW vs the 576 GB/s that both the Mobile 4090 and M4 Max have). For reference, a desktop 4090 will have 165.2 Tensor FP16 TFLOPS (FP32 Accumulate) and 1008 GB/s MBW. Bottom line: line, if you're doing local training, don't use a laptop unless you *really* have to.

[jonathanofrivia]

today i was thinking that it would be good to see this subject on your channel and boom! here it is! thanks as always ❤

[pewpewpower]

This is one of your best videos yet! Excellent content organization, pacing, charts📊, the detailed recs and scenario analyses. Just wow.

Keep it up!👍

[jonathantran]

7.5 minutes in.. just wow, amazing data, love how you present the different processors, and the tier chart for fan noise/heat is incredibly helpful

[copacialex]

Wait what?! I don't believe it is possible to use a laptop for something different than content creation. It should not be allowed! 'Sad' thing is that who needs a laptop for other stuff then 'EXPORTING MASSIVE 4K VIDEOS" they already know what they need or want. However, this is a great educational video and very professional. Thank you!

[lilunchengsmiles]

As a machine learning engineer, the best laptop for my work right now is the Apple MacBook Pro. The primary reason is its unified memory, which allows me to load large language models directly into my 96GB M2 Max MacBook Pro and get used by GPU—something no non-Mac laptop currently offers. This feature is invaluable for prototyping and testing models efficiently.

Secondly, for machine learning work, we often spend significant time manipulating data in Pandas data frames, and for reasons beyond just clock speed, the Apple M-series chips consistently outperform x86 chips in these tasks. With the release of the M4 chip, this performance gap has only widened.

Lastly, Windows simply isn’t ideal for data science. Many libraries don’t install smoothly on Windows due to various compatibility issues. While the Windows Subsystem for Linux (WSL) is helpful, achieving the full benefits often requires maintaining a separate Linux OS, which adds complexity.

[Ty.mauricee]

I just started studying data science so this is the perfect video for me, thanks josh👍🏾

[PKperformanceEU]

Josh, just because most 13gen intel laptops are loud and hot doesn’t mean all are like that.

I have the asus zenbook pro 14 ux6404vv with 4060m
And yes i had to replace the thermal paste and i use a self made fan control-curve software i wrote in C#

Now i can exactly control the fans the way i want. Its a 13700H laptop, gets 108/1112 on CB2024 and GPU can sustain 125w.

Its very quiet unless pushed and now with my controls always cool to the touch!

By the way its for sale since i move to macOS. Region Europe

[nilaypatel]

Kudos Josh for bringing up this content!

[edreilima]

Tysm Josh!

I waiting soooo long for this video!

[YuraL]

Numpad is the most important requirement whenever I buy a laptop, a 16'' display is rather a nice bonus. I do some basic ML/scientific calculations using Python libraries, so for me CPU, especially single-core productivity is super important. I bought a Lenovo ThinkBook 16 G6 IRL, it's perfect for my needs.
- i7-13700H up to 5 GHz
- 32 GB DDR5 5200
- 1 TB NVME SSD
I don't know why you pay so much attention to screen resolution, it's important for large displays >21'', but for laptops, it seems overvalued.