Here's how you train a model in the cloud for free: kzread.info/dash/bejne/fphs2LKbpNywh7Q.html

@Matlockization

Жыл бұрын

If vram is low then can extra ram get you over the line ? Like 16, 32 or 64GB ?

@JesperDramsch

Жыл бұрын

@@Matlockization No they're connected to a different kind of chip and aren't interchangeable.

@Matlockization

Жыл бұрын

@@JesperDramsch I see, thank you.

@cattnation6257

3 ай бұрын

Help me should I buy black diamond from dell

@cattnation6257

3 ай бұрын

@@JesperDramsch please help because I am new to these developments I want to be future proof so in near future I don't need to buy more

This channel needs way more subs! The content is high quality / well explained. :)

Man, this is so so helpful :) Many thanks for patiently covering all the key concepts !

@JesperDramsch

2 жыл бұрын

Of course!

Great advice. Because I've been looking for a second machine for my deep learning research. Now, I will switch my strategy from a local machine to the cloud. Thanks.

Loved this video, Jesper. Thank you!!! I’m happy I came across your channels

@JesperDramsch

Жыл бұрын

Thank you, Rebeca! Welcome in.

You are so very correct. Especially for newer AI developers, long training times are not the norm. We use RTX through H100’s for most of our AI development- at least on the training side. However for coding, data sci work, inference and UI/UX we all use our favorite OS, whichever that is. One thing to keep in mind for pro level large parameter/data set AI dev, you will often be using a dedicated server running in the kilowatts with AI grade TPU/GPU’s (e.g. V100’S, H100’s, etc). Whether owned, hosted or otherwise, few jobs will be run locally.

Excellent information!

Thanks a lot, man! Very useful tips

@JesperDramsch

2 жыл бұрын

Glad I can help

Thanks a lot for making such a helpful video man.

@JesperDramsch

10 ай бұрын

Thanks for stopping by! Glad it's so helpful!

Very helpful! Thank you so much.

@JesperDramsch

Жыл бұрын

Glad it helped!

That was really helpful. Many thanks

@JesperDramsch

Жыл бұрын

Glad it helped!

Very very helpful 👏. Thanks alot .

@JesperDramsch

2 жыл бұрын

Glad to help!

What a great video!

great video, thank you!

@JesperDramsch

Жыл бұрын

Thanks!

Thank you for this. I'm interested in ML for advancement in my career and your explanation is helpful.

@JesperDramsch

2 жыл бұрын

I'm glad! Thanks for stopping by!

That is really helpful!

@JesperDramsch

2 жыл бұрын

Thank you!

Thank you Jesper!

Thank you very much!

Thank you You just saved me from getting broke 😅 I was thinking of getting a pc but confused on what graphics card to get

Nice video. Very clear explanation

@JesperDramsch

2 жыл бұрын

Thank you!

Already owned a Acer Nitro 5 with RTX 3070 mobile + R7 5800H. Still watch you full video :). And my laptop can train 90% types of model after I cramp up the virtual memory => 80 GB (from 16GB of RAM 😂). I'm very satisfied with my $1500 laptop

Nice video!

Hi Jesper and tank you for your video, informative as usual. I'd like to ask you what you think of a laptop with a Ryzen 7 5825u and no GPU, but with the intention of connecting a "prosthetic" desktop GPU in the future through a pcie connector; I'm talking about something like the EXP GDC "THE BEAST". Or do you think it's easier and better just using an external GPU through thunderbolt 4?

Just discovered your channel and I'm already a fan of you. I have recently started learning data Science, currently learning python and statistics. Looking forward to your guidance through this channel.

@fianekosaputra417

2 жыл бұрын

So, what laptop is your choice?

@AamirSiddiquiCR7

2 жыл бұрын

​@@fianekosaputra417 Right now I'm using my old samsung np300e5c laptop to learn python. I'll be buying an AMD 6000 series laptop with rtx 3060 once it comes out

@JesperDramsch

2 жыл бұрын

Thanks so much Aamir! Good luck on your journey.

@joelsabiti4828

Жыл бұрын

How far have you gone since?

Thanks man

I got myself an m1 air a couple of months ago. One thing I dislike is that tensorflow has multiple issues with Mac. It's better to learn about scaling and deploying first, because clouds are always available, rather than throwing a large amount. As for whether it's worth it when you're very advanced in the field, I'll update when I get there 😂 Side note I have a 3070 but I realised model design, preprocessing plays more of a part in ML.

@JesperDramsch

Жыл бұрын

Agreed. Thanks for the follow-up!

@waynelau3256

Жыл бұрын

@@JesperDramsch thanks for replying, you made want to leave an update since the time I commented. The M1 air is very strong when it comes to smaller models, especially if you're working with scikit learn. Very snappy with pandas as well. But leave the LLM/ CV models to the cloud or a GPU. Just one month after the comment, I ssh/remote into my home PC for most of my ML work. Or do my training on my work server. Overall, I personally feel that one should not buy a laptop while considering for ML/AI. It's not worth it. Get what suits your use case. For me I'm quite happy with a smaller screen as I need to carry my laptop around and I work on the commute. I also do not game so mac is fine. Hope this helps someone out.

@JesperDramsch

Жыл бұрын

@@waynelau3256 love this Wayne. It's similar to my experience. Happy to train scikit-learn on my phone. Not gonna get a laptop for DL / LLM

Was looking for an EDC work laptop that can handle personal scoped AI ML on my own air gapped network at home. That way i can leave the models and data private and connect the laptop by cable to train the model when needed. Appreciate this extremely detailed information and how it all relates to AI and ML. My very own private air gapped AI 😀 sounds like I'm better off setting up a tower AI build and go with maybe a laptop with one of the new intel core ultras for otg edc.

hello, I really loved your video, I have a question, I am a computer sciences master degree student and I am taking courses like machine learning, deep learning and artificial intelligent, do you recommend the macbook air M1 or should I go for a pro or promax? I need it for my studies. thank you very much for your help.

Nice coverage of laptop configurations for ML.

@JesperDramsch

2 жыл бұрын

Thanks!

That's a good one, you can do deep network also on a cpu and for small models is even faster then a gpu. About using the cloud I have a different take, I'm using one computer for browsing and ome for training. 😂

Hello @Jesper, Some python library's use Intel mkl and other Intel specific optimization ..... How much performance does this effect in your experience when compared to AMD. Should we just avoid amd cpus for ml work?

Very good, thanks.

@JesperDramsch

Жыл бұрын

Thanks hazel!

@biohazel

Жыл бұрын

@@JesperDramsch I ended up sticking to Colab and buying a Raspberry Pi to assemble a Bitcoin node instead. Indeed, no need to go too far on a hardware trip, especially for starters.

I understand your point but I don't fully agree about your sentence when you say (with my words) "a CPU with just a load of RAM will be enough"... I'll explain why: Though you are right saying we have to prioritize RAM, but CPU is important too...try training a model with Weka workbench (java based) on you laptop or desktop computer... a fast CPU will help. Students will do deep learning and not necessarily limit themselves in machine learning with scikit or whatever framework. so... a) Having a lot of RAM yes but with a very good CPU too... most probably when working with MLmodels is because you are probably working on an application that requires many components where all are not necessarilly ML based. You could design a NodeJS driven UI that will interact with some back end that you still develop onto your computer and that will serve the model. In order to make it in a very efficient and organised way, you will endup with containers and there is why you'll need CPU and RAM (though they are lightweight). b) because of (a) you will probably start diving in both DEVOPS techniques and MLOPS paradigm. Both of them will require automation which will also consume CPU. Especially if you build a C++ or Java application that must be built. c) because of (a) and (b) your computer will start to gain some load just to work all these things. d) Though an NVIDIA RTX is quite expensive, it can help you a lot on doing deep learning tasks and allow TF to use the onboard GPU. there you will face interresting issues. You'll probably hit during training the VRAM limits and will have to work hard but learn in order to get a really good neural network architecture running on your machine. e) You talk about using cloud, yes I agree partly, this is only for experienced people. Other will get hard time to make it work (I am not talking about Google colab or any other fantasy stuff). Therefore you will travel from (a) to (d) on your local machine. Personally I follow you and agree on what you say about using open sytems and not using macs. 2 years ago I bought a Linux Laptop with an onboard NVIDIA RTX. Because of the budget I could only afford an RTX3600. But I could have a very good intel i7 16 vcpus and 32 GBRAM. All that for less than 1800€ with a wide screen (17"). But that was 2 years ago. Today I would go for a more robust RTX card and smash 64GB or 128GB RAM directly. The only thing I think I would recommend in that... is the battery, choose good ones and chose a laptop with spare batteries. Also, because you will work with Docker containers and perhaps have many versions of the virtual environments in Python... think about the disk space => I recommend today MINIMUM 2TB of SSD. If you can afford more, better it is. Then yes using a cloud solution is also elegant but you'll still need to consider an efficient laptop too because of (a) to (e)..

@jayakumar4633

10 күн бұрын

Could you please recommend any old workstation laptops thank you

@alexandrevalente9994

9 күн бұрын

@@jayakumar4633 mine is a Clevo. Go to Laptop with Linux. But today, 2 years after, things have evolved a lot and i would consider run Tensorflow onto Mac OS. But i still haven't bought it. But certainly it Will be more expensive but there you get An M chip.

Hi! I am also starting to to learn AI and ML now. Can you please help me with a few things. 1) After what amount of time will I need a better laptop or can I do it on my current laptop? Right now I have an office laptop with intel i5 10gen U Processor with integrated graphics 2) Since I am starting to learn where should I start for AI & ML? 3) Is Asus ROG Flow X13 2023 a good option? It has Ryzen 9 7940HS and Nvidea RTX 4050 6GB (60W). I want this one because it is super portable and would also help in taking notes since it is touchscreen. Also is 16GB RAM enough in the laptop? It would be great if you could help me out a bit. Thanks!

So, what is your suggestion for a person who is planing to get a laptop for ML/DL workloads?

Any market recommendations? I waa told the Lenovo Yoga is a great buy, I am new on this topic. What do I need to get on memory etc?

Could you please recommend any old workstation laptops

Hi given that I will do the learning on cloud but it may not be always available while travelling. So, what minimum configuration would you recommend. I am a beginner and student . I travel so I have to also carry a work laptop. portability is a concern. I thought MacBook Air with m1 but ram could be concern. Can you suggest minimum ram, processor, gpu(if needed) and other.

The M1's run very cool and you don't need to worry about running long tasks even in the fan-less one. All 1st gen M1's have a maximum of 16GB of (V)RAM(including the iMac), M1 Ultra has a maximum of 128GB of (V)RAM. Unified Memory also removes the PCI bottleneck between VRAM and RAM, with a bandwidth of up to a combined 0.8TB/s.

@beytulk

Жыл бұрын

How is the compatibility of python packages? As I see on the internet, many people still face issues. I'm willing to buy an m1 and pursuing a career in data science and ml, so I will be using python a lot. Also I'll use docker for some of my classes in school. I'm very very indecisive because of the incombatibility issues.

@yagoa

Жыл бұрын

@@beytulk There are not any alternatives were you would have any type of portable device(w/o being plugged in all the time to run anything locally). I have not had any issues, I think the issue has been that pytorch was slow to update, by the time you have your system up I don't think anything will be missing. About 0.1% non M1 software on my system now, at launch it was about 40% so it has been a really fast transition from a dev perspective.

@forlorn8025

Ай бұрын

​@beytulk which laptop did u buy?

@yagoa

Ай бұрын

@@forlorn8025 M1 Air 16GB and thermal modded it at launch, no issues

@yagoa

Ай бұрын

@@forlorn8025 M2 and M3 are just overclocked slightly more efficient M1 versions M4 will probably be the first worthy upgrade for ML with acceleration on CPU and GPU + better NPU

Such a helpful video! I need an update for 2024 products. Can't decied on which laptop to buy.

@JesperDramsch

3 ай бұрын

Thanks! Honestly it mostly still holds 😅

is it big difference between dedicated or integrated? I want to buy expertbook core i7 -32 RAM BUT it has iris xe .is this gpu enough for my works as you said???

Hello Jesper, Thank you so much for the fabulous, informative and helpful video ever made on KZread about Machine Learning laptops. But wait I've a question for you. I'm thinking about buying an M1Pro 16 inch with 16gb of RAM base model and use it for machine learning purposes, of course I wanna keep this laptop for a while but I'm afraid buying it then find out that it's not powerful enough to handle machine learning and data science stuff. Well I'm between the hammer and the anvil. (The costs and the needs). I hope you're gonna be able to help me choose and take a final decision. Thank you Jesper!

So for a windows user the lenovo ideapad 5 would be a perfect option you think?

Will the Acer swift X be a good choose ?(It has a dedicated GPU)

Should I consider buying a normal Laptop with Intel Iris Xe if i work in AI , ML, DL or some gaming laptops Nvdia RTX , GTX gpus ? Btw I am a non gamer

The new Intel Xe gpus have support for machine learning via OpenVino. Intel seems to be pushing this really hard. In fact the whole Xe gpu architecture is designed around being multipurpose matrix specifically for doing lots of computation necessary for ml.

For PhD students, maybe it's better to access a University PC from your MacBook from home :D

@JesperDramsch

3 жыл бұрын

Definitely, as long as the university has a GPU server or GPU desktops. It's exactly what I did actually!

Lovely video! Can you make a video about Open/Free Website and Database to test/learn Machine Learning Model? Please...

@JesperDramsch

2 жыл бұрын

Definitely. Check out my shorts for sme inspiration on that already!

Excellent

@JesperDramsch

2 жыл бұрын

Thank you!

Hello I am new i mean new what is the best computer for ai laptop or desktop to do crypto and stock picking i was told to start with a lapton so i can learn the data and software stuff what is your thoughts

For windows, when you say ram.. Is refer to RAM or gpu ram?

ur right my laptop is really aerodynamic... i find myself playing frisbee with it all the time

@JesperDramsch

Жыл бұрын

Ultimate frisbee or fetch with a retreiver dog?

how about the performance of RTX2050 in deep learning? I'm considering a I7-12700H + RTX2050 laptop

This was really cool. I bought old server GPU and put it into a big desktop PC Case with a hydroponics fan to cool it down. Got a 24gb tesla card for usd$300 that is about as fast as a 1070ti

@JesperDramsch

2 жыл бұрын

That's very cool!

0:42 I felt that

I try the classical ML in my old Linux machine. It works very well. As you said in the video, it is a better idea to run Deep Learning in Cloud service. BTW, if I create and use my own data for creating a Deep Learning model in the cloud service, it will be guaranteed that my model and my train data set will belong to me?

@JesperDramsch

2 жыл бұрын

That's awesome. Normally yes, if you go with any of the mentioned services it's your property

How many gb of ram should the laptop have for neural networks

I tend to buy a laptop with ryzen 7 pro 6850U. Is AMD good for who begin learning machine learning ? Hope your response.

could you help me , ERAZER MEDION laptops are good for neural networks?

We're due for an updated video after the m1x Mac

@JesperDramsch

2 жыл бұрын

Isn't the successor to the M1 the M1 Pro and M1 Max after all instead of m1x?

I'm preparing to train on two laptops, Dell Precision 7550 with Quadro T1000 dedicated graphics, 64MB RAM and Windows or Dell Precision 7520 with 16GB RAM and Quadro M1200 (it's not even supported by Rapids, so we'll see). Maybe this year I will buy PC with nVidia 3070 or other new card, depending on the market offer (we'll see how Intel ARC will behave with AI).

@aymen5777

7 ай бұрын

Were they any good? (The dell precision laptops)

How about running Mindspore on Macs and laptops with Nvidia?

This was the first video of yours I ever watched and when I started I thought, naaah a new MacBook Pro could surely be fine for training models. I can't tell you how wrong I was. The hype is very different from reality and you are 100% correct. I have had to embed so many special cases into my training pipeline to support MPS (METAL) and even then support for torchvision is still incomplete in V2. I ended up going for an rtx4090 on a separate headless Linux server and it reduced training time on my use cases by an order of magnitude.

@JesperDramsch

Жыл бұрын

I appreciate that feedback!

@alzeNL

8 ай бұрын

METAL is worthless IMHO - having a mac here in multiboot OS, the Radeon chips in the imac dont really hold a candle to the nvidia GPU's for ML.

Cool video. I had a choice to make between 8GB and 16GB mac. I will take a 16GB now.:) Thank you!

@JesperDramsch

2 жыл бұрын

Love to hear it!

Thank you for this. Is there a need to offer an update to this video given that it is now two years later?

@JesperDramsch

Жыл бұрын

Maybe replace M1 with M2 that's it.

Great video Jesper. Can I ask u? Wud be better laptop with i7 1260p and 64gb Intel Iris graphics xe or i7 12700h, 32gb, Intel Iris Xe too but having gpu RTX 3070 8gb? Second little more price about 250€. Thx for your help.

@Itachi-c137

7 ай бұрын

I would also like advice on this. Please.

What's your take on new macbook pro models, am planning to get the 14 inch base model, will that be enough, should I upgrade anything in it like Ram, more CPU and GPU cores?

@JesperDramsch

2 жыл бұрын

What is your main use case? NLP, computer vision, tabular data?

@kevinmccallister7647

2 жыл бұрын

@@JesperDramsch I'm looking at picking up the new Mac book pros and my main task is learning ML and DL - I'm interested in computer vision object recognition, speech to text and NLP what would you recommend?

0:43 lmao I hope that's edited, cause my soul damn near left my body when I heard that sound

@JesperDramsch

2 жыл бұрын

This shall be forever a mystery 🙃

I do not suggest a macbook for ML. I have a fully beefed out M1 Max, even with big ML frameworks like tensorflow starting support ARM, that's not main issue. The main issue is the package manager. Your computer will be your "entire" development environment, and developers know the ass-pain of dependency hell. The apple package manager is absolute garbage. You may be able to use an updated framework for M1, but that doesn't mean you'll be able to use the code everyone else is producing with other frameworks and libraries, or more importantly the prior version of pytorch or tensorflow. Get a PC and install a linux distro with a good package manager.

Video recommended days after I bought a full Desktop Computer

@JesperDramsch

2 жыл бұрын

Don't feel bad. I'm still rocking a full desktop PC and I wouldn't change for the world.

Great explanation video! One thing I would have liked to hear more about is dominance of the Nvidia CUDA framework. It seems to me that a lot of ML python libraries are compiled to work with the CUDA framework and therefore one would need to run it on Nvidia hardware. That’s the advantage that Nvidia has because it started 20 years ago developing the CUDA framework and was miles ahead of everyone else in the field of deep learning. As you said, things like Tensorflow is just starting to have Apple silicon /aarch/arm64 architecture. But Nvidia continues to innovate with RAPIDS (CUDF vs. Pandas) and with their NVLink on their DGX A100 and DGX H100 (8 GPUs w 80GB VRAM each and all linked together). However, with respect to laptop for ML, would it make sense from the perspective of a DevOps use case? Rather than using the laptop to train a huge LLM (llama2 , falcon40b, mistral, etc.) what if I just want to test a few of the prepackage Nvidia NGC containers in docker and add some additional python packages/libraries to them and test training on a smaller dataset smaller model to confirm that things work and then move the container over to the Cloud like Amazon AWS and run it on Nvidia A100 or DGX A100 resources to do the full training? Would laptops with nvidia GPUs (for docker, kubernetes, VMware) for DevOps testing purposes be useful or not at all? Thanks.

If I have a pc with ryzen processor and amd integrated gpu can I still use it to access a cloud service? Sorry for the dumb question, I'm fairly a noob in this

@JesperDramsch

2 жыл бұрын

No worries, we all start somewhere. The cloud is literally a different computer, so as long as you have internet and some sort of PC you're fine!

One question is has Apple with it's unified memory (shared memory between all its processors - CPU/GPU/Nueral, etc.) overcome the speed of handshaking of data required when having separate VRAM?

@JesperDramsch

2 жыл бұрын

That is honestly way beyond my knowledge. Sorry

Pls What do u advice, i wanna get a laptop for Deepfacelab 2.0 to make deepfake vids Here are my laptop specs ; MSI raider ge78hx, corei7 13700hx Nvidia RTX 4070 8gb Vram 32gb of memory 1tb. Second laptop is; MSI stealth gs77 Intel corei7 12thgen Nvidia RTX 3070ti with 8gb vram 32gb ddr5 memory 1tb Are these specs good enough to run deepfacelab and get decent results?

Agree with many things here, great video! However, using cloud GPUs is cheap at first sight, but letting a model train for days on cloud GPUs might be much more money than your electricity bill and cost you in the hundreds (with a sizeable model) and should be considered into the whole calculation. Cloud GPUs range from 0.2 €/hr (single 3090) up to 4€ /hr (multi-A100), a discrete GPU might pay off in less than a year depending on your project.

@JesperDramsch

Жыл бұрын

It's a consideration for sure. But if you're running a model for multiple days straight, I would try and dissuade from a laptop regardless and go for a desktop or server-solution. It'd be really annoying to have a laptop that has to stay on for days on a power outlet.

@chrisk7332

Жыл бұрын

@@JesperDramsch you are right - I kind of ignored the fact your specificly talking about laptops - more used to SSHing next to my GPU

@JesperDramsch

Жыл бұрын

Agree there

Hey there! Love it! Great video, really useful. So, I just started my journey (MS in Data Science), and sure thing, I need to upgrade my PC. I want a laptop since it is better to work at any place, but I'm really confused about all this stuff, processor, GPU, RAM, and so on. I don't have a big budget, so I wonder what should I prioritize? Thanks to your video, I understand the first thing is RAM! Is it 16Gb RAM enough? And second, I've heard each processor is good depending on the specific task, talking about Ryzen and Intel, which one could be better, especially if I will have to work later in my projects and other small programming tasks? thank you in advance for taking a few minutes to help me with my doubts.

@JesperDramsch

2 жыл бұрын

I think 16GB should be plenty in a laptop. For most normal tasks you'll be happy with it. As for processors, it pretty much doesn't better. I like AMD, but I think you'll be happy with either.

Nowadays with LlaMA models we might can run some models on our laptops

@JesperDramsch

Жыл бұрын

Llama has 65 billion parameters. Are you sure?

Hello, i am getting into data science and after looking at your videos i feel dedicated graphic card is not a necessary requirement (at least for someone who is learning to code). I am contemplating thinkpad, 16gb ram and amd ryzen 5 pro processor without any dedicated graphic card. I have had a gaming laptop from dell and to be honest they are not at all reliable so I am refraining getting one for data science work. Thinkpad is reliable as what i have seen from reviews of lot of consumers. What do you suggest?

@JesperDramsch

2 жыл бұрын

Those sound like good considerations

@quantum3712

2 жыл бұрын

@@JesperDramsch thanks for your valuable information. Looking forward to learn from you. 🙏

@JesperDramsch

2 жыл бұрын

@@quantum3712 you're welcome. Hope it works out for you!

Thanks for your recommendation with that cloud you suggested. I will try that! Though, I write deep learning networks also for my own projects in computer vision and would prefer not to use a cloud. Also because that requires internet access and I also enjoy working at places where I sometimes don’t have internet. Therefore, I’d appreciate a video about good laptop options for that purpose. P.S. It needs to be compatible w/ Fedora or Ubuntu distro

@JesperDramsch

2 жыл бұрын

Do you have power where you don't have internet?

@stellamn

2 жыл бұрын

@@JesperDramsch to work for 2h outside it’s sufficient when my laptop is fully charged. Obviously, I will not let a very deep network learn for several hours if I just planned to go outside for 2h. In that time I would either build parts of the architecture or some test to try something out.. some ideas for architectures.. etc.

@JesperDramsch

2 жыл бұрын

@@stellamn that makes sense. I'd go for portability anyways then. Build it offline. Make tests offline then train in the cloud later when you're back. Otherwise see that you get a laptop with a compatible Nvidia card and enough RAM if you still want to train on your laptop.

@JesperDramsch

2 жыл бұрын

A pc like that will not be very portable though oftentimes. They get heavy and it can very power draining.

@stellamn

2 жыл бұрын

@@JesperDramsch don’t worry, I did already my own research and found some possible solutions. Thanks for your suggestions :) (I didn’t see the prior message)

Thank you so much for your exposition. I just got into machine learning at the start of the year (so 6 to 7 months at the time of writing). I have a gaming laptop with 6GB of VRAM but I find that it's not the GPU that's utilized when I'm training ANNs. So I've been considering the M1 Macs because of the inbuilt neural engines. Could you make a video detailing them, just as you did the GPU?

@JesperDramsch

Жыл бұрын

I'll put it on my idea list. Thanks!

@zainkhalid472

Жыл бұрын

Your GPU was not being utilized because you need to explicitly write code to run it on GPU. Like you will need to select Machine for processing and then move your matrices (arrays) into tensors etc..

@ostensibly531

Жыл бұрын

Buying a different Machine won't solve your problem.

I am working in java, python no-sql & bigdata. And want to learn NLP & deep learning. I'm looking for a durable laptop. My intention to buy a gaming laptop is learn to deep learning only. Not for gaming. I would like to buy Omen Ryzen 5800H with Rtx 3060 6gb or Legion Ryzen 5600H with Rtx 3050 4gb. I have two questions- 1. Will you suggest to buy a gaming laptop to learn ML/DL? 2. Suppose I am working on a java application, a non gpu task on that laptop. Will gpu run all the time? Will it effect the laptop longevity due to heat generation? Please advice.

@JesperDramsch

2 жыл бұрын

6Gb and 4GB is very small for modern-day applications, like I said in the video.

@himavanthkumar5269

Жыл бұрын

Hi I am in the same situation like you - please suggest best laptop. Can I go for gaming laptop.

I trained a CNN on the MURA dataset (40k mri’s). My MacBooks battery swelled and the whole top case had to be changed 😅

@LewiUberg

2 жыл бұрын

Btw! I used my macs gpu with plaidML, but it doesn’t look like it’s being maintained anymore 😫

@JesperDramsch

2 жыл бұрын

That's terrifying. I hope it was under warranty 😱

@LewiUberg

2 жыл бұрын

@@JesperDramsch yes! Or else I would be crying still 🥴 now I write most of my code locally, then upload to colab for training.

@JesperDramsch

2 жыл бұрын

Very relatable.

Is that legion 7 you are using. Im a student and i am planning to get one.

@JesperDramsch

2 жыл бұрын

I'm afraid not, sorry.

can i use amd latest gpu RX6000 series to learn deep learning and machine learning???? hope to get your reply soon

@JesperDramsch

2 жыл бұрын

At the moment it's still very difficult on Radeon cards. So for now I'd say no.

This is a useful video, but having tried tensorflow-metal on osx/mac its just not ready (in 2022) - the particular piece of work I'm doing sees the ML RNN network come to a screeching halt after several hours, the issue has been replicated by Apple Developers, but they have yet to offer a fix, in the meantime I cannot do any development on my mac. Because I have to run the model, I went for a gaming laptop that is CUDA compatible, in 2022 I was able to pick up a laptop with 4G of video ram for less than £800 - that is alot, but compared to running ML/AI GPU on cloud providers, a better and cheaper development environment (An EC2/P3 for Horovod costs £3.59 an hour in eu-west-2). I've only just found your channel and will subscribe, but I think for 2022 this video could be updated as there are some good gaming laptops with nvidia chipsets that a fully CUDA comapatible that allow tensorflow to run natively.

@harishvarkannadasan5555

11 ай бұрын

@alzeNL can you recommend me such laptops in 2023?

@alzeNL

8 ай бұрын

@@harishvarkannadasan5555 hello, just revisting this video and saw your comment - the laptop I use for ML/DL is a ASUS TUF Gaming F15 - It takes some tweaking, but even some of the largest RNN will load, it just takes time for them to produce the models, but still cheaper than cloud computing!

Laptops are aerodynamic 🤣🤣🤣🤣🤣🤣...

@JesperDramsch

Жыл бұрын

💸

@TheStallion1319

Ай бұрын

I liked the expression 😅

I am a Data Science student and my laptop specs are low but can I use only cloud for the projects?

@JesperDramsch

2 жыл бұрын

At least in the beginning you should, yes.

@pratikthakur5052

2 жыл бұрын

@@JesperDramsch Okay Sir, thank you !

helpful video thanks, are you a german native ?

@JesperDramsch

2 жыл бұрын

Yeah, I'm from the North. Thanks!

RAM is the key. At least, from my experience in ML.

Best comments ever on buying laptop for ML

@JesperDramsch

2 жыл бұрын

Thanks Raj!

Dude i dont know is it enough for me? For beginner = rtx3060 , 32gb ram , i7 12th gen , 512gb ssd (Hp Victus 16) . Is it ok for me? What do u think?

@JesperDramsch

Жыл бұрын

That's a pretty beefy PC. I'd hope it works for most consumer models

@Itachi-c137

5 ай бұрын

@@JesperDramsch Will a i5-12450h with a gtx 1650 and 64gb ram be okay?

Tensorflow has issues with M1/M2 macbooks.

Is jumping to a 32 gb RAM from 16gb worth it if you are going to be training a lot of Deep Neural nets (mostly Natural Language processing)

@JesperDramsch

2 жыл бұрын

Probably. It just means you can fit twice the data in loading/preprocessing. Not having enough RAM can be annoying

@Duge6124

2 жыл бұрын

@@JesperDramsch thanks 👍 Great and informative video by the way. If you are buying the new Macs please do another one in depth like this. I believe people around the world are looking for this kind of content

@JesperDramsch

2 жыл бұрын

@@Duge6124 will do!

@DaarioNeharis

2 жыл бұрын

@@JesperDramsch its weird that your video comes in my recommendation when I just faced the problem of my 32 gb ram not enough.. upgrading to 64 gb now.

@JesperDramsch

2 жыл бұрын

@@DaarioNeharis Google knows 😂

Hei, can you name some Cheap laptop not Mac, for a beginner who want to self learn python and later artificial intelligence for under 800$ ,

Does the new AMD GPU work with deep learning ?

@JesperDramsch

Жыл бұрын

It's getting better, but often it doesn not.

this high-pitch sound you heard most likely came from capacitors

@JesperDramsch

Жыл бұрын

Possibly. Might also be coil whine though.

Hi Jesper, congrats on reaching a 1K Subs. Especially like your calm style of communication in your videos. I am an absolute beginner in Data Science and I was wondering if you have any advice on how to get more practical info on the ground realities of this field. Few initial questions that I have are... What's the right balance between Math\Stats vs Programming. When to start with your first project. What are the ground realities in job market, which data science skills are valued over others etc.. (I would be going through your video on the ideal projects to avoid)

@JesperDramsch

2 жыл бұрын

Thanks for the kind words! The right balance? That's hard to say honestly. Make sure you have a bit of both at least. Start your first project as early as possible. It's the best way to learn.

what shoud i get for my graduation project. My teacher wants me to use the below techniques: -Logistic Regression -Support Vector Machine -Random Forest -Decision Trees

In fact macbook are not that expensive - maybe 1,3 of a dell or 2x of a new Acer :) but a little used macbook with nice layout/look can go well under 1000euro. I still dont recommend but they are not expensive that much - if you dont need 10 macbooks

what about amd gpus like r5500m ?

@JesperDramsch

2 жыл бұрын

For now AMD GPUs will not work, it has to be a Nvidia GPU. Also mobile GPUs often have less oomph than their desktop counterparts (the m after the number).