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Another excellent lady in the lecture hall. Great India!

Nice ma'am

Thank you so much madam

Very nicely explained

Please provide repo Link.

When will the RNN lecture be released?

This lady is simply excellent!

super analogy and well prepared teacher!

thank you

What was that error mam??

code files or git repo?

This mam is very knowledgeable guys please listen carefully .......😊

Thanks Dr. Aruna for the explanation. One suggestion, you can try using disappearing lines while explaining the code to temporarily highlight the code that you are explaining, instead of cluttering the entire page with un-necessary lines.

Good knowledge depth!

Happy to see you sir. It’s been 17 years.

Can you pls share the GitHub repo for the code notebook.thanks

Not sure who his audiences are. Seems like he don't have any confidence of them understanding what he is presenting. Frankly, this was very well explained. He points out the subtleties of what is happening in the agentic application. A good primer on agentic application development using Langchain. Hope the code can be shared. Thanks

There is no explanation, just reading the slides in the video!

Very good teacher. No AI can ever replace a good teacher.

Very nice explanation Sir. Can you please share the jupyter notebooks too? So that we can try the assignment

What an informative video 👏 👏 👏

Thanks 😊

Excellent explanation 👍

Good explanation

hahaha explanning zero to mastry pytorch progame

Hmmm.... I wonder if its right to say that adding layers improves model performance unless of course the complexity in the task/data demands to. I often find that a data deep dive or understanding the data is an essential step that is ignored to really determine how to improve model performance.

We are fortunate to come across this session on Transformer by Neil sir. Looking forward for more sessions from Neil sir.

Mam more disturbance while recording

May you please provide the link to that article?

Great lecture! The only thing I would like to add is that the Transformer LLM architecture being discussed here is decoder only architecture and not encoder. As per Jay Alammar's book Hands-On Large Language Models which is the book being used here as a reference, any pink blocks with a chat symbol at the top right corner represents Decoder-only models.

Thanks for the forecast! I need some advice: I have a SafePal wallet with USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). What's the best way to send them to Binance?

As a professor, you can do a lot of rosy things other than training a transformer

I am really impressed the way professor teaches, the depth of understanding he has on topics he isteaching as well as the simple way to convey difficult topics to make people understand is awesome. Is there a way I can get his contact or any course where he has taught this end to end.

Nice to see you teaching. I was your student 25 years back

Thank you

Electrical transformers dont convert ac to dc 😢

amazing

Thank you so much Prof. ❤

👍🏻

Superb Explanation

Great explanation, Sir!

Sir ultimately your explanation is awesome

clear explination

@32:53 Am I reaching Question I visualise the chatGPT producing multiple answers for the same question at parallel windows

Superb Explanation and your voice makes us interesting on the subject

Woww so nice to see the OG himself on RUclips. Good job KMIT . Thank you for giving us the opportunity to learn from you again after a decade 😊

Sir Very Nice Explanation

Kmit means ?

I just completed the playlist ma'am. It was awesome , and adding the timestamps with topics will make it mroe easy to navigate to the topics . =>Kindly add the TimeStamps

great teaching thanks for the wonderful explanation 🙏