courseraАнализ данных

Fundamentals of CNNs and RNNs

Курс от Sungkyunkwan University

Начальный≈ 5.5 чКорейский

О курсе

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.

Навыки, которые вы освоите

Recurrent Neural Networks (RNNs)Deep Learning Natural Language Processing Image Analysis Computer Vision Machine Learning Convolutional Neural Networks Artificial Neural Networks

Программа курса

5 модулей · 13 учебных материалов

01Week 1. CNN Basics3 материалов

Week 1. CNN Basics

New ReadingЧтение New VideoВидео week1Задание

02Week 2. Convolution and Pooling3 материалов

Week 2. Convolution and Pooling

Учитесь у экспертов

Jee-Hyong Lee

Professor, College of Software