• Ashish Premji Nitnaware
• Dr. Sharvari Govilkar

The objective of modern finance is to discover effective methods for comprehending, processing, and interpreting stock market data into knowledge that may be used to make better investment decisions. Financial tasks usually have many different and complex structural characteristics which are influenced by a wide range of political and economic circumstances, and frequently have unexpected, dynamic, nonlinear, time-varying, and changeable structural qualities. Powerful software recently developed using machine learning techniques can extract useful data from a huge database. The whole people involved with this domain will not be expert. It is always be a requirement of system which can predict the share trands.in this study researcher developed a system using machine learning classification model namely k Nearest Neighbor (KNN), SVM algorithms, Adaboost, and decision trees. The developed system takes date as input and predicts categorical output for next date market trends.

"Prediction System for Stock Market Indices Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 10, page no.c280-c285, October-2022, Available :http://www.jetir.org/papers/JETIR2210234.pdf

"Prediction System for Stock Market Indices Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 10, page no. ppc280-c285, October-2022, Available at : http://www.jetir.org/papers/JETIR2210234.pdf