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This is exactly what I wanted for my project

It is possible to share the google doc that describes used in the hands-on workshop. Thanks

This video caused a clash of Nikunjs in my team

Nice Video, can we get the github link code for practising it

This is really awesome! Thank you very much.

Nice explanation thanks mam 👌

Excellent video, full of incredibly useful information, and very well presented.

Great, Could you share the resources used for this video? Many thanks

15:40 I'd add here a Task which is more 'main' than any other task. QA must understand what they do and why, they must understand business domain itself. Thank you for the video.

Hi, how to export to onnx using cuda?

can you give me an example notbook to do this. in video.

Nice, but it should be better to split into chapters, first 1 hours was setting up on AWS. Thank you.

Amazing structured breakdown of the problem.

Hello Kartik/TH-cam Handler, I have just joined a company as a Machine Learning Engineer Intern and still a fresher. I would like to keep my Name and where I work anonymous for this specific platform. I am working on a task where I need to analyse the dataset I have been given and convert that data into text using LLM. Example Data: Date Temperature 2 Feb 30C 3 Feb 24C Example Output: Today's weather will be warmer than yesterday and a little pleasant.... <so on> The use case is a little different but this is just an example to explain what I actually want. A little more explanation: What I want is that the LLM to read the dataset completely either through an excel I have or any format like CSV and answer my queries or create a conclusion based on the dataset I gave. I would love to get some help/insights from someone as experienced as you on how I can achieve my goal. We can connect on some other platform if you are comfortable with it. You can contact me at me personal mail: rohitkhare998@gmail.com Thanks. regards, Novice ML Engineer

Awesome talk. I am preparing for a privacy preserving ML interview and this was an amazing crash course. Second, for the thermal flu issue you mentioned, can't we just use FHE or SMPC like you mentioned in the slides?

Well explained!! thank you !!

For f****s sake turn the damn phone off

For f****s sake turn the damn phone off

Very good tutorial, specially the MLServer part

Helpful!

Do you have demo video for this? And not able to access the github

Great talk! As suggested, we do see now more "small" LLMs trained with considerably larger amounts of tokens than the "compute-optimal” recommended by the Chinchilla scaling laws

Great stuff. Really looking forward to more content like this! Props @AI-Makerspace

This talk is amazing. Completely nailed it.

Repo link in description or comments will be helpful

Thanks for the very good overview of training distributed systems on kubernetes, would love to see more detailed information making all the pieces fit together !

Well done, Stefan!

Finetuning e.g. Mistral LLM should perform way better than BERT. In practise, we typically finetune LLM model for the task.

Great talk!

fantastic

Great talk!

It is too good thank you for this wonderful workshop

Can you please let me know where can I find the presentations and note books ?

Is there still a link somewhere to the slides?

I have found the link of the docs in case anyone needs it . docs.google.com/document/d/1zbPak5aDFcMgEIYbDmL_F9N0GHptvoobxP9GpQlesmk/edit

Promo`SM

Grate session. Thank you guys

great explaination

lack of clarity in ppt

plz take care of the clarity its really shitty

Great session

This is intellectually beautiful and useful

the 1080p is the same as 360p

👍👍🎉🎉❤️👍

fanstastic demo! thank you so much

Can you share the sample code as well ?

nice

Where to find the demo notebooks?

These are amazing presentations but the slides are a bit blurry on all the videos on your channel, would be great if you could fix that in the future. Thank you.

ugh why do so many of these recordings have bad audio