Stock Market Forecasting Using LSTM Neural Network

This study investigates the widespread use of machine learning techniques, including recurrent neural networks (RNNs) and long short-term memory (LSTM) models to analysis stock market data. By utilizing RNN LSTM model capabilities identify temporal relationships patterns in data, it seeks overcome conventional techniques' constraints. The research provides empirical proof efficiency RNNs enhancing investment decision-making by analyzing project outcomes using real-world inclusion this paper strengthens exploration techniques analysis.