From Machine Learning to Deep Learning: Advances in Techniques to Practical Applications

Dr. Jayeshkumar Madhubhai Patel

Artificial Intelligence, Deep Learning, Engineering, Systematic Literature Review, Neural Networks, Machine learning algorithm, Deep neural network architectures, Cybersecurity, Network intrusion detection system and Ensemble learning

The complexity and increasing frequency of cyber threats necessitate the development of advanced detection systems capable of identifying both known and emerging attacks. In this study, we present a hybrid Network Intrusion Detection System (NIDS) based on anomaly detection, which integrates several machine learning and deep learning algorithms, including XGBoost, Random Forest, Graph Neural Networks (GNN), Long Short-Term Memory (LSTM), and autoencoders. The study investigates the realworld application areas in which ML and DL techniques are implemented. Moreover, the study highlights the latest trends and possible future avenues for research and development (R&D), which consist of developing hybrid models, generative AI, and incorporating ML and DL with the latest technologies. The study aims to provide a comprehensive view on ML and DL technologies, which can serve as a reference guide for researchers, industry professionals, practitioners, and policy makers.

Published Paper   E-Certificate

"From Machine Learning to Deep Learning: Advances in Techniques to Practical Applications", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.11, Issue 1, page no.a873-a876, January-2026, Available :https://ijsdr.org/papers/IJSDR2601091.pdf

Volume 11 Issue 1, January-2026

Pages : a873-a876

Paper Reg. ID: IJSDR_306926

Published Paper Id: IJSDR2601091

Downloads: 000249

Research Area: Science and Technology

Country: -, -, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2601091

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2601091

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition