The Attributes of the stock or security exchange continuously changing over year. While only one thing which cannot be change in the stock market i.e. volatibility, It is the most powerful technique because can make money while sleeping by investing money in the stock market. In our project we make a website, That is predict performance of stock asset in the future and help the user in which company they should invest so they can make maximum profit. For this predictions we various types of machine learning algorithms, But in recent studies suggested that support vector machine(SVM) is most commonly used for make precisions, Which is lead to the look-ahead bias, Which was later tackeled by the coupling it with the window approach to improve the accuracy of the algorithm. But on other hand we use the linear regression algorithm to making the predictions. The results which is produced by the website shows that our method is more accurate than the support vector machine(SVM). Furthermore, If any new user visit the website which does not have any knowledge about stock investment for such a users we can links to the various articles and videos which is brush up his knowledge.

Stock market prediction using machine learning is highly effective to predict the future prices of the stock with minimum investment. This paper proposes the system that will predict the future prices of the stock of different companies this prediction will help a investor to take decisions to maximize profits. This paper shows that by using different techniques like support vector, LSTM, linear regression future prices of the stock can be effectively predicted.