Paper Key : IRJ************084
Author: Piyush Goyal,Jasbir Singh,Anurag Goyal,Dr. Vijay Samyal
Date Published: 10 Nov 2024
Abstract
Deep learning machine is one of the biggest components of artificial intelligence whichstudies all other study fields and can achieve capabilities that were previously only performedby human intelligence. This paper provides a comprehensive overview of fundamental deeplearning technologies such as neural networks, convolutional architectures, recurrentarchitectures, transformers, and generative adversarial networks (GANs). It also reviewsfoundational developments in hardware, software frameworks, and cloud computing thathave fuelled advances in deep learning. For instance, we emphasize applications acrossdiverse areas of computer vision, NLP, and healthcare. However, deep learning is not withoutits difficulties: the requirement of massive datasets with a high computation power, theabsence of interpretability and ethical issues such as bias and fairness. It also discussespossible future directions, such as explainable AI, few-shot learning, and sustainability, aswell as the need for responsibly developing the techniques to realize the full potential of deeplearning.
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