HBRP Publication Page 23-29 2023. All Rights Reserved Page 23 Research and Reviews: Advancement in Robotics Volume 6 Issue 1 An Efficient Model for Stock Price Forecasting using Long Short Term Memory Sleeba Mathew C 1 , Ahmed Unaish 2 , Mahammad Akbar 3 , Mahammad Ishan 4 , Mahammed Dhansih Raza 5 1 Department of Computer Science and Engineering, Yenepoya Institute of Technology , Mangalore, Karnataka 2,3,4,5 Department of Computer Science and Engineering, P. A. College of Engineering Mangalore, Karnataka *Corresponding Author E-mail Id:-sleebamathew2005@gmail.com ABSTRACT One of the most challenging tasks in the realm of computation is stock market forecasting. Numerous factors, including physical ones, physiological ones, rational and irrational behaviour, investor attitude, market rumours, etc., have a role in the prediction. These factors all work together to make stock values unpredictable and highly challenging to forecast accurately. In order to predict future trends, we use Machine Learning (ML) algorithms using past stock price data. To forecast the price of stocks in the future, we employ the LSTM (Long Short Term Memory) model. LSTMs are crucial because they can store previous or past data, which makes them extremely effective in solving problems involving sequence prediction. This is crucial for market prediction since it allows us to accurately estimate future stock values by storing and reading historical stock data. With the help of Dash, a Python framework, and an LSTM recurrent neural network, we have developed a single-page web application that displays company information (logo, registered name, and description) and stock plots based on the stock code (ticker) provided by the user. Additionally, the ML model allows the user to obtain predicted stock prices for the N number of days they have input. Keywords:-Predicting, LSTM, investor, stock, accuracy. INTRODUCTION The ability for investors to purchase and sell shares of firms with public listings is provided by one or more stock exchanges in almost every nation. There is a secondary market here. According to regulatory regulations, the promoter group must sell a substantial percentage of the shares to the general public when a firm first registers itself on any stock market to become a public corporation. During the company's primary market trading period, promoter groups or institutional investors buy shares of the company. After the promoter has primarily sold the shares to retail customers or on the secondary market, shares may be exchanged on stock exchanges. The National Stock Exchange (NSE) and the Bombay Stock Exchange are India's two busiest stock exchanges (BSE). 200 firms are listed on the NSE, compared to 5000 on the BSE. The trading procedures, market opening and closing hours, and settlement procedures are the identical on both exchanges. Thanks to a trading account and a Demat account, stock exchanges enable individual investors to participate in the stock market and to purchase even a single share of a listed firm. Numerous internal and external factors have an impact on a company's stock price.