• Seetu Patel
• Dr. Jitendra Agrawal
• Varsha Sharma

OD is a Data Mining Application. Anomaly contains boisterous information which is explored in different areas. The different strategies are now being explored that is more conventional. We reviewed on different procedures and uses of OD that gives an original methodology that is more helpful for the novices. The proposed approach assists with cleaning information at college level significantly quicker with incredible precision with the assistance of AI calculation. This study incorporates the current exception strategies and applications where the loud information exists. Our paper characterizes basic audit on different methods utilized in various utilizations of exception recognition that are to be investigated further and they gives a specific sort of information based information for example more helpful in research exercises. So where the Anomalies are available it will be distinguished through OD methods and checked in like manner.

Outlier Detection (OD), Data Mining, Machine Learning (ML)

"Outlier Detection for Data Mining using Deep Learning Neural Network: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.a93-a100, May-2023, Available :http://www.jetir.org/papers/JETIR2305014.pdf

"Outlier Detection for Data Mining using Deep Learning Neural Network: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppa93-a100, May-2023, Available at : http://www.jetir.org/papers/JETIR2305014.pdf