Transformers for beginners | Hindi

Understanding Transformers:
Transformers, one of the most groundbreaking architectures in artificial intelligence! In this video, we break down the key components and workings of the Transformer network, explaining its significance in natural language processing and beyond.
Paper link: arxiv.org/pdf/...
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In this video, we dive into Transformers, a powerful type of neural network that has changed the way machines understand and generate language. We’ll explain how Transformers work, including key concepts like self-attention and the roles of encoders and decoders. You’ll see how this technology powers applications like translation and chatbots, making it a game-changer in artificial intelligence. Whether you’re new to AI or looking to expand your knowledge, this video will give you a clear understanding of Transformers and their impact!
#transformers

[@pifordtechnologiespvtltd5698]

Commendable

[@CodeWithAarohiHindi-h5b]

Thanks!

[@Sunil-ez1hx]

Awesome

[@chiragsahoo8708]

Great work 👏

[@CodeWithAarohiHindi-h5b]

Thank you so much 😀

[@soravsingla8782]

Superb

[@CodeWithAarohiHindi-h5b]

Thanks 🤗

[@2107mann]

Nice... Good job

[@CodeWithAarohiHindi-h5b]

Thank you so much 😀

[@AhsanAkram-z8w]

Excellent explanation. But listen at 2x for better experience
Thanks for your explanation mam.

[@CollegeOnline]

Thanks allot super arohi mam, highly appreciated, will be waiting for other videos in Hindi like vit and swin transformer network explanation in details for classification detection and segmentation 🙏

[@CodeWithAarohiHindi-h5b]

Sure

[@zakiriqbal1605]

Wow . hat's off to you and thanks you for helping us in a very easy method . kindly keep making videos for us

[@CodeWithAarohiHindi-h5b]

Thank you! Glad my videos are helpful and yes, I will definitely make more videos 🙂

[@motahseenfarhankhatib6402]

"Absolutely brilliant explanation, Arohi! 🌟 You made understanding Transformers so much easier with your clear breakdown of the key components and their significance in AI. The way you explained the architecture, especially its impact on natural language processing, was top-notch! Looking forward to more insightful videos like this. 👏🔥"

[@CodeWithAarohiHindi-h5b]

Glad it was helpful!

[@Asadkhan-nz6qm]

Thank you, mam, please also make videos on vision transformers as well.

[@CodeWithAarohiHindi-h5b]

Sure, Soon!

[@Asadkhan-nz6qm]

@@CodeWithAarohiHindi-h5b Mam I have a question I am confused here about where the word ""mujay"" comes from as you said we feed the word mujay in Mask Multi-Head Attention.

[@CodeWithAarohiHindi-h5b]

@@Asadkhan-nz6qm "Mujeh" is the word word translated in hindi from "I" in english

[@Asadkhan-nz6qm]

@@CodeWithAarohiHindi-h5b Mam i know the word mujeh comes from I but I want to know the mechanism is this coming from the last encoder or the first decoder?

[@soravsingla6574]

Plese keep sharing such an informative content

[@CodeWithAarohiHindi-h5b]

Sure 😊

[@mabdulkabirkhan]

What is the input to first decoder?

[@CodeWithAarohiHindi-h5b]

After processing, the encoder gives a set of vectors for each word. These vectors contain information about the relationships between words. The decoder needs an initial word to start generating its output. This is usually a special token like . So that means the decoder takes the encoder's output and the token to produce the first word of the output.

[@mabdulkabirkhan]

@@CodeWithAarohiHindi-h5b Ok Thank you.

[@AhsanAkram-z8w]

Finally Subscribed

[@CodeWithAarohiHindi-h5b]

Thank you!