This course covers fundamental concepts of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which are widely used in computer vision and natural language processing areas. In the CNN part, you will learn the concepts of CNNs, the two major operators (convolution and pooling), and the structure of CNNs. In the RNN part, you will learn the concept and the structure of RNNs, and the two variants of RNNs, LSTMs and GRUs. The goal of this course is to give learners basic understanding of CNNs and RNNs. Throughout this course, you will be equipped with skills required for computer vision and natural language processing.
WB
Korean lecture. His explanation is very good. Easy to understand but simple deep learning concepts are required.한국어 강의라서 매우 이해하기 쉽습니다. 설명을 아주 쉽게해주십니다. 한국인 분들에게는 추천합니다.
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the teacher speaks in korean language, I can't understand.
I would really like to take this course but the video's are in Korean (including subtitles). Please try to get translation done so I can take this course. Thank you.
In My Opinion, this course is the best CNN and RNN course. the professor's explaining for important concepts are really easy and intuitive. I've never heard that kind of explaining.
I strongly recommend this course.
Korean lecture. His explanation is very good. Easy to understand but simple deep learning concepts are required.
한국어 강의라서 매우 이해하기 쉽습니다. 설명을 아주 쉽게해주십니다. 한국인 분들에게는 추천합니다.
지금까지 봐왔던 모든 강의들 중 CNN과 RNN을 가장 알기쉽게 설명해준 강의였음.
It is a really useful course, especially for those who learn Data Science for the first time like me.
The lectures are in Korean, use subtitles
I study this lecture again
이해하기 너무 쉬워요!! 감사합니다
good course!