Stock Prediction and analysis Using Supervised Machine Learning Algorithms

Abstract

Using Supervised Machine learning, our project is to analyzed and predict the stock value. As due to pandemic situation stock market trading is the most learned and become important activities to earn money as a second source of income in the people of India. The concept of predicting a stock's future worth is known as stock trading or stock prediction. Stock market is difficult to understand and to predict the value of stock. The majority of stock traders utilize various analytical techniques, as well as time series analysis, when seeking to make stock forecasts. So, we need a better tool to get out of this contemptuous situation and help the common man to make profit. In this research, we discuss a Machine Learning strategy that will be taught using publicly released stock data to build information, then using that information to make a valid prediction.For accuracy and prediction of stock Classification and Regression Algorithms are used with Kaggle dataset a machine learning technique comes under supervised learning that are Random Forest, Decision Tree, and Logistic Regression to predict stock prices for the given company previous year data, employing prices with daily trading prices. Python is the coding language used to anticipate the stock market using machine learning. Result come across that Regression model has more accuracy and can predict more accurate stock price.