
The Great Pirate Era of AI has begun.
sorryhyun96
Free
Beginner / Deep Learning(DL), LLM
4.6
(54)
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Beginner
Deep Learning(DL), LLM
To keep up with recent deep learning trends, we examine the context of deep learning's groundbreaking advancements.
428 learners
Level Intermediate
Course period Unlimited
Reviews from Early Learners
5.0
똘똘이스머프
Thank you for the valuable lecture. Have a happy new year.
5.0
쿠카이든
It was a time to learn about deep learning. Thank you!
5.0
Jang Jaehoon
Wow! It's hard! But I'll try to get something out of it!
Concept of 'Trend' in Deep Learning
Why deep learning emerged in this modern form, understanding its 'research context'
"I've read the SOTA paper, so what do I do now?"
"Have you tried Tensorflow? Even my 16-year-old daughter can build machine learning models with it."
"You want me to listen to a presentation at an international conference? How on earth do you do that?"
No matter how rapidly deep learning research advances, the latest research is still based on previously defined problems. A thorough understanding of these problems, organized by theme, allows you to immediately grasp the value and significance of the latest research. Therefore, through this lecture, I aim to intuitively convey the key points behind the recent groundbreaking advances in deep learning and the challenges currently facing the deep learning academia and industry.
This lecture covers research trends through 2023 and will be uploaded sequentially, starting with the Generative Models chapter.
Background of the emergence of representation learning
Elements for Effectively Developing Learning Techniques
Understanding abstract and difficult concepts such as Transferability and Uniformity
Development stages of generative models and the evolution of discourse
Background of the emergence of the Large Language Model
Distinction between Interpretability and Knowledge: Two Criteria Continued to Be Required for LLM
The Relationship Between Knowledge and Memory
Characteristics of adversarial gradient
Adversarial interactions between Gradient, Representation, and Model elements
We have been involved in various seminars aimed at conveying intuitive and accurate concepts, with the goal of sharing knowledge through activities such as fake research institutes.
He has diverse research and practical experience, including serving as a SIGUL 2024 workshop program committee member, ACL 2023 emergency reviewer, EMNLP 2023 invited reviewer, and publishing history in the Journal of the Korean Information Science Society.
For more detailed information, please refer to the notion resume .
Who is this course right for?
For those curious about cutting-edge deep learning issues.
For those gradually doubting Korean Google data.
Need to know before starting?
Person who has fully completed at least one course from the Stanford/MIT OCW series
Or those who have completed a degree program from a computer science educational institution such as Coursera, Udemy, etc.
Basic understanding of Linear Algebra, Mathematical Statistics, and Calculus
2,908
Learners
94
Reviews
1
Answers
4.4
Rating
4
Courses
Hello, I am Seunghyun Ji, an IT consultant at Vaim Consulting Group.
Please refer to the following link for a detailed introduction.
Hello, my name is Seunghyun Ji, and I am working as an IT consultant at Vaim Consulting Group. Please refer to the following link for a detailed introduction. https://inf.run/rzZVT
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18 lectures ∙ (3hr 4min)
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