Stock Closing Price Prediction Using Deep Learning, TensorFlow, and Keras

Stock market forecasting is a particularly difficult undertaking because it is dynamic, non-linear, and dependent on a number of factors. This model helps the ones who are interested in the stock market and wants to gain profit from it. By comparing the proposed methodology value to the actual value and utilizing the evaluation metrics RMSE and MSE, the model is put to the test. The goal is to have a model that is able to predict the closing price of the stock by evaluating the previous stock prices which will help the investors while buying or selling the stocks. The objective is to build a Deep learning model capable of accurately predicting Stock closing prices, identifying the key features that significantly impact stock prices and providing visualization by improving supervised learning. The proposed method will utilize a supervised learning approach, RNN to predict stock closing prices.