Coursera
Free Online Course (Audit)
Korean
Paid Certificate Available
5 weeks long, 5-6 hours worth of material
selfpaced
Overview
Class Central Tips
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 (convolutionand 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.
In the CNN part, you will learn the concepts of CNNs, the two major operators (convolutionand 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.
Syllabus
- Week 1. CNN Basics
- Week 2. Convolution and Pooling
- Week 3. Structure of CNNs
- Week 4. Recurrent Neural Network
- Week5. LSTM GRU
Taught by
Jee-Hyong Lee
