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Everything About RNNs | TTT Transformer Lecture Free Release

How do RNNs process sequential information? We’re releasing the RNN section of TTT: To The Transformer for free. Gain an intuitive understanding of how recurrent neural networks work and build a foundation for studying attention and transformers.

7 learners are taking this course

Level Basic

Course period Unlimited

RNN
RNN
Deep Learning(DL)
Deep Learning(DL)
RNN
RNN
Deep Learning(DL)
Deep Learning(DL)
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What you will gain after the course

  • Understanding the Basic Structure and Operating Principles of Recurrent Neural Networks (RNNs)

  • Understanding how previous information carries over to the next step when processing sequential data

Recommended for
these people

Who is this course right for?

  • Those who have learned the basics of deep learning but still find it difficult to understand how RNNs work

  • Those who want to build a solid understanding of RNNs before studying attention and transformers

Need to know before starting?

  • Fundamental Concepts of Artificial Neural Networks and Deep Learning Training

  • You don’t need to know about Transformers beforehand. This is suitable for those learning or reviewing RNNs for the first time.

Hello
This is hyukppen

Hello. I’m Hyeokpenheim, a deep learning instructor with a Ph.D. from the KAIST School of Electrical Engineering. After working as a principal researcher at Samsung Electronics and as an adjunct lecturer at the School of Medicine at Sungkyunkwan University, I currently run Hyeokpenheim Academy. I am the author of *Easy! Deep Learning*, an introductory book on deep learning, and have 11 years of teaching experience, having taught approximately 3,000 students in total. I specialize in deep learning theory and PyTorch practice, covering CNNs, transformers, LLMs and vision models, diffusion, and more.

Rather than simply memorizing model architectures or equations, I explain why each idea emerged and how it works. Starting with intuitive analogies, I clarify the meaning of the equations and connect them to code, with the goal of helping learners explain what they have learned in their own words and build a foundation for reading papers in depth.

On the YouTube channel “Hyukpenheim,” we offer lectures ranging from basic mathematics and Python to advanced deep learning topics, as well as providing on-site lectures and training for schools, companies, and organizations.

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