Deep Learning: Concepts, Types, Applications, and Implementation

Subject Areas : Machine Learning

Fereshteh Aghabeigi ¹ , Sara Nazari ² , Nafiseh Osati Iraqi ³

1 - Department of Computer Engineering and Information Technology- Arak Branch- Islamic Azad University- Arak- Iran.
2 - Department of Computer Engineering and Information Technology- Arak Branch- Islamic Azad University- Arak-Iran.
3 - Department of Computer Engineering and Information Technology- Arak Branch- Islamic Azad University- Arak-Iran.

Received: 2021-11-05 Accepted : 2022-03-02 Published : 2022-10-01

Keywords: deep learning, Neural Networks, Machine Learning, Network training,

Abstract :

Today, deep learning has attracted attention in various scientific and non-scientific fields. Deep learning is a branch of machine learning that simulates the human brain for various applications like recognizing voice, face, handwriting, identifying kinship, image processing, and etc. In deep learning, a set of representation algorithms is used to model high-level abstract concepts through learning at different levels and layers. Deep learning has become popular due to its capabilities like automatic feature extraction, high extendibility, and wide application in different fields. In this paper, it is tried to describe different deep learning models and architectures, how they are trained, and the required hardware and software structures.