[Important] Learn Various Concepts of Generative AI | Transformers, Attention, and Vector Database

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Feb 16, 2024, 9:01:45 PM2/16/24

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Dear All,

Can foundational concepts like Transformers, Attention, and Vector Database be calculated by hand? Yes, here's how:

Professor Tom Yeh recently developed 14 exercises that dive deep into the core of Generative AI, showing us that even the most advanced concepts can be understood from the ground up.

These exercises cover a wide range of topics, from the basics of vector databases to the complexities of generative adversarial networks (GANs) and transformers.

[1] Vector Database
https://lnkd.in/gTanDTMj

[2] Self Attention
https://lnkd.in/gDW8Um4W

[3] Transformer
https://lnkd.in/g39jcD7j

[4] GAN
https://lnkd.in/gyKzNGDy

[5] LLM Sampling
https://lnkd.in/gwe69_84

[6] Backpropagation
https://lnkd.in/gsiU2uc2

[7] Autoencoder
https://lnkd.in/g2rM9iV2

[8] Dropout
https://lnkd.in/g4KHF-Hd

[9] Batch Normalization
https://lnkd.in/gVjknYkU

[10] Mixture of Experts (MOEs)
https://lnkd.in/gPFdQdsW

[11] Recurrent Neural Network (RNN)
https://lnkd.in/gDANw4iH

[12] Mamba
https://lnkd.in/gGcS2sMa

[13] MLP in Pytorch
https://lnkd.in/gnjif8mX

[14] Matrix Multiplication
https://lnkd.in/gXKnQQF3

Reference:

Thanks & Regards

Dr. Prashant Singh Rana,

Associate Professor,

Computer Science and Engineering Department,

Thapar Institute of Engg. and Tech., Patiala, Punjab, India.

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