As we know in today’s world managing expenses is a very challenging thing. By analyzing our previous expenses, we can predict our upcoming expenses. Now digitalization is everywhere so we can get bank transaction history easily, just by getting the data from transaction history we can predict the estimation of upcoming expense. We can do this using machine learning, machine learning is used in many things one of them is prediction. We are using linear regression algorithm, it is a machine learning algorithm used in prediction. The main aim of this project is to build a system that helps in managing personal finances of the user. This project has mainly three modules, first is to collect the data and prepare it to be used in algorithm, next is to build a network between the algorithm and the dataset. The last one is prediction in which system is going to predict the expenses. Particularly we are predicting the expense of next month. We can also use this system in stock market for predicting the next step if stocks of a company will rise or fall do, this can help us in making money from stock market and manage our expense.
Stock Market Prediction with Gaussian Naïve Bayes Machine Learning Algorithm
