Technical Paper on Stock Prediction using Machine Learning Algorithms

In today's financial world, a stock market is quite important. The stock market's worth is an important part of today's global economic system. The stock market attracts a large number of people from all areas of life, whether corporate or academic. Because of the non-linear structure of the stock market, research is one of the world's hottest and most important topics. People invest in the stock market based on previous theory outcomes or assumptions. When it comes to forecasting, people typically look for ways or procedures to help them reduce risk and improve performance. As a result, in today's competitive stock market, stock value forecast is crucial. Critical and technical studies' approach cannot guarantee the consistency and accuracy of estimations. As a result, machine learning technology has risen in popularity in stock forecasting over the last 5-6 years, with estimates based on current stock values that have been educated in terms of prior values. This research focuses on using LSTM (Long Short Time Memory) technology to forecast future market trends.