Prediction of Stock Prices using Machine Learning (Regression,Classification) Algorithms


The stock market is an interesting industry to study. There are various variations present in it. Many experts have been studying and researching on the various trends that the stock market goes through. One of the major studies has been the attempt to predict the stock prices of various companies based on historical data. Prediction of stock prices will greatly help people to understand where and how to invest so that the risk of losing money is minimized. This application can also be used by companies during their Initial Public Offering (IPO) to know what value to target for and how many shares they should release. So far there have been significant developments in this field. Many researchers are looking at machine learning and deep learning as possible ways to predict stock prices. The proposed system works in two methods - Regression and Classification. In regression, the system predicts the closing price of stock of a company, and in classification, the system predicts whether the closing price of stock will increase or decrease the next day.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL