STOCK PRICE PREDICTION

Abstract

Machine learning has many important applications in the stock price prediction. Here, we will discuss about predicting the returns on stocks. This has uncertainties and it is a very complex task. This project will be developed into two parts: First, we will learn how to predict stock price using the Long Short-Term Memory neural networks. Predicting stock market prices involves human-computer interaction. For stock market analysis, conventional batch processing methods cannot be utilized efficiently due to the correlated nature of stock prices. We suggest an algorithm that utilizes a kind of recurrent neural network (RNN) called Long Short-Term Memory (LSTM), where using stochastic gradient descent the weights are adjusted for individual data points