In today's financial landscape, stock trading stands as a cornerstone activity. Stock market prediction, the art of forecasting the future value of traded financial instruments, is a vital pursuit for investors. Traditionally, stockbrokers rely on technical, fundamental, or time series analysis to make informed predictions. However, the advent of machine learning has revolutionized this field, particularly through the use of Python programming language and advanced techniques like Long Short-Term Memory (LSTM) networks, a subtype of Recurrent Neural Networks (RNN). LSTMs, renowned for their ability to model sequential data ,have emerged preferred choice for analyzing time series and sequence-based tasks, including stock price prediction.