A Comprehensive Review of Recent Advancements in Machine Learning: Emerging Trends and Future Directions
Machine Learning, Deep Learning, Transformers, Federated Learning, Quantum Machine Learning, Explainability, AI Ethics
Machine learning (ML) has seen unprecedented growth in recent years, driven by deep learning, large-scale datasets, and new computational paradigms. This paper reviews significant breakthroughs in ML, including self-supervised learning, transformers, federated learning, neuro-symbolic AI, and quantum machine learning. We discuss their impact on key industries such as healthcare, finance, and autonomous systems while addressing challenges like explainability, bias, and computational efficiency. The paper also outlines future research directions to bridge existing gaps and enhance ML's real-world applicability.
"A Comprehensive Review of Recent Advancements in Machine Learning: Emerging Trends and Future Directions", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 3, page no.b187-b189, March-2025, Available :https://ijsdr.org/papers/IJSDR2503123.pdf
Volume 10
Issue 3,
March-2025
Pages : b187-b189
Paper Reg. ID: IJSDR_301017
Published Paper Id: IJSDR2503123
Downloads: 000159
Research Area: Science and Technology
Country: ujjain, madhya pradesh, India
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
