Discovering the Diversity of Neural Networks: An In-Depth Analysis of Architectures and Applications

Amandeep Kaur; Gagandeep Jagdev

Discovering the Diversity of Neural Networks: An In-Depth Analysis of Architectures and Applications

Authors: Amandeep Kaur, Gagandeep Jagdev

Unique Paper ID: 165720
Volume: 9
Issue: 7
PageNo: 963-972

Keywords: CNN FNN LSTM Neural Networks RNN

Abstract:
This research paper explores the evolution, principles, and applications of neural networks, a cornerstone technology in artificial intelligence and machine learning. Neural networks are computational models inspired by the human brain's neural connections, comprising interconnected nodes organized into layers. The paper delves into the fundamental concepts of neural networks, including Feed-Forward and Recurrent architectures, backpropagation for training, and various types of activation functions. It examines how neural networks learn from data through supervised, unsupervised, and reinforcement learning paradigms, emphasizing their ability to extract meaningful patterns and make accurate predictions from complex datasets. Furthermore, the research explores cutting-edge applications of neural networks across diverse domains, such as computer vision, natural language processing, speech recognition, and autonomous systems. Case studies and empirical results demonstrate the efficacy of neural networks in solving real-world challenges, ranging from medical diagnostics and financial forecasting to autonomous driving and personalized recommendations. Ethical considerations and challenges in neural network deployment, including issues of bias, interpretability, and scalability, are also discussed. The paper underscores the importance of responsible AI development practices and regulatory frameworks to address these concerns and ensure the ethical use of neural network technologies. In conclusion, this paper provides a comprehensive overview of neural networks, highlighting their transformative impact on technology and society. By synthesizing current research trends and future directions, it aims to guide researchers, practitioners, and policymakers in harnessing the full potential of neural networks while addressing critical challenges in their adoption and implementation.

email to a friend

Cite This Article

ISSN: 2349-6002
Volume: 9
Issue: 7
PageNo: 963-972

Discovering the Diversity of Neural Networks: An In-Depth Analysis of Architectures and Applications

Available:https://ijirt.org/Article?manuscript=165720

16 Jun, 2024

Augmenting Cloud Performance: An In-Depth Analysis of Algorithms for Data Security

10 Jun, 2024

UNVEILING PATTERNS IN TIME SERIES FORECASTING MODELS - ARIMA, ARIMAX, VAR

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now

Latest Publication

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry