• Amey Nandgaonkar
• Anil Nandgaonkar

Trading holds a pivotal role in the global financial market, being one of its most crucial activities. The inherent unpredictability of stock market forecasts adds to the complexity of this task., however, various approaches and methods that are used for making predictions about the stock market. The prevalent method for achieving accurate stock market predictions involves the utilization of AI and ML-based techniques. This analysis leads to the conclusion that stock market prediction is a highly intricate task, necessitating the consideration of various factors to enhance accuracy and efficiency in forecasting the market's future. A comprehensive literature survey has been conducted, revealing a diverse range of methods available for predicting the stock market. In this paper, stock market prediction, using artificial intelligence and machine learning is depicted by analyzing the stock market. Various algorithms and different tools have been used for prediction and applied that understanding to make a AI and ML model to predict the future stock prices

Stock Market, Prediction, AI/ML models, Data Sources, Python, LSTM, LGR, SVC, ANN, Regression algorithm

"A Comparative Analysis of Machine Learning Models for Stock Price Prediction ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.h317-h324, July-2025, Available :http://www.jetir.org/papers/JETIR2507741.pdf

"A Comparative Analysis of Machine Learning Models for Stock Price Prediction ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pph317-h324, July-2025, Available at : http://www.jetir.org/papers/JETIR2507741.pdf