can i connect like 8 bad cpu´s? and train with that?

Watch the full course here: skl.sh/4cKzvqB

Thankyou so much for this video

The music. Make it stop! jk. But please consider toning it way down. Thanks.

This was very helpful!!! Thank you ❤

Thanksssss 🎉

Technically g in gpu stants for general it was just used for graphics alot so it shifted now its returning to true aka general but you need cuda and tensor cores

Anything changed since this video? Any plans to make complete beginner videos on how to take your own data, and train a model on it (using local and/or cloud GPUs like AWS,GCP/GoogleColab)? I see so many (open-source?) models on HggingFace (LLAMA, Qwen-2.5-Coder-32b, etc), but have no idea how billions of parameters I need, or what they represent?! And assuming you download one of these terabyte-sized models that have been pre-trained, you still have to train it some more with your own local data? How? Alternatively, you upload your data and train it the cloud? At what do you need to know/learn things like PyTorch or TinyGrad? I assume the models themselves are binary blobs, and so you must work via some kind of API? How does ChatGPT's MyGPTs and Claude's "Personal Projects" fit into this?

Minisforum MS-01 i9 13900H 32gb ddr5 ram (max 96gb) and 1tb for 900euro is a great base to start if you dont want a big machine ....(with cloud service)

I LOVE how you just got straight to the point

Instructions unclear : Bought an AMD Rx 7900XT

I'm watching in 2024 and my machine i7 11800h with rtx 3060 it works like a beast 😊😊. So for now no need to upgrade to new machines.

Wait you got back early August

@JesperDramsch I'm just starting out with some ML/AI projects, and I already know I'll be working with fairly large datasets. I'd be interested in hearing your opinion on whether it would make sense to use my current Mac Pro with these specs by installing an Nvidia RTX 4090 and running Linux: 3.3 GHz 12-Core Intel Xeon W 256 GB 2933 MHz DDR4 Or do you think it would be more efficient to build a separate setup? Obviously, building a separate setup would cost me more since I work with Macs and I wouldn’t want to sell my current Mac. What do you think?

What about RTX 4090 for deep learning?

I'd say that using macBook Air 15" and Ryzen based PC = both at price of single macBook Pro - does offer best value. And as far as upgrade is considered - first, do math Ph. D.

your GEFORCE RTX is an NVIDIA card right? got confused!

Wow thank you a lot i feel like i understand a lot better

2024 is this advice still relevant? Eg using only nvidia for deep learning

My bro how to setup my 2x 3090 for machine learning ..they collecting dust now.sub +like even if u dont answer

How is rtx 2050

good video! keep up the good work

I am a complete computer novice and this video was soo helpful. Thankyou

Hello sir , I have an i7 12th gen laptop with no gpu and looking to learn deep learning on it can my laptop handle it with colob or kaggle

when you use generative AI features in Colab, Google collects your prompts related code, generated output, related feature usage information, and of course your feedback

If Im a pyshician and need to have data privacy? I can't just use an online notebook and lie about it in the paper 😅

is it good to use the x-elite notebooks for machine learning and deep learning?

This is a really good video! i stumbled here and got close to buying NPU mini PC. However, I think I am okay running Gemma 2 Ollama and learning. Thank. Subscribed!

Thank you 😊 I got all 3 now

Tremendo trabajo de investigación, gracias por tomarte el tiempo para recopilar toda esta información y resumirla.

for gpu's unless you're a deep learning guy with loaded pockets, it is not worth it to buy some rtx laptop or something with low vram, simply because these things require a LOT of computing, the free kaggle gpus are better in that regard

Can I do Ho 15 s

you tube algo gods finally decided to give me a relevant video rather than click baits

Most people keep pondering whether to buy an SUV when they actually need is a cycle.

no one care if you have PHD or any sort of that, just don't tell that right at the beginning of the video, no one care

well it depends on the complexity of the task. suppose you’re working on time series forecasting, you could do that with either scikit or tf/pytorch which are ML or DL respectively. by following the tf/pytorch approach you may get better results due to the NNs, but this approach demands heavy requirements like CUDA for parallel computations and accelerate the process. Meanwhile, if you are satisfied with slightly worse and cardinal results, you could just stick to ML which don’t demand much

I am intersted in 4D seismic inversion for prediction SW, Sg or pressure. I go through your github but I do not see the data input, could you please share with me about that. I am also reserching apply ML in oil&gas specially in geoscience. Many thanks for your sharing!

Could you please recommend any old workstation laptops

Hugging face,keras,kaggle 🎉🎉

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!

Awesome post. Can you elaborate a bit more on the mechanics of content based filter. Thanks a lot

Thank you for a wonderful work and sharing the application of ML in Geoscience. Really appreciate it.

Thanks man

He is so pretty...

want a video on classification vs clustering, ummm, more of a supervised giant vs unsupervised giant !!

Do I need upgrade my Gtx 1660Ti GPU?

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.

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

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.

Thank you Jesper!