The Process of Teaching Students in the Deep Neural Network Laboratory Work

被引：0

作者：

Docheva, Lilyana ^{[1
]}

Dochev, Ivo ^{[1
]}

Manev, Stoycho ^{[1
]}

Lubih, Ludvig ^{[1
]}

机构：

[1] Tech Univ Sofia, Fac Telecommun, Sofia, Bulgaria

来源：

2022 30TH NATIONAL CONFERENCE WITH INTERNATIONAL PARTICIPATION (TELECOM) | 2022年

关键词：

education; distance learning; deep neural network; machine learning; Pytion;

D O I：

10.1109/TELECOM56127.2022.10017260

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

The various software availability for deep neural network implementation enables students easy and accessible implementation of different tasks in a wide area range. The ready for use applications using, for many of the deep neural network training stages is not related to a deeper understanding of the deep neural network theory. For this reason, the authors of this paper have developed an exercise with students' participation as many of the stages of the deep neural network training as possible. This paper presents one solution for laboratory exercise process organization in distance learning in deep neural network area. Each stage of the student's work is examined in detail. The specifics of its distance learning implementation are also discussed.

引用

页数：4